A workshop to showcase the diversity of scientists to middle school students.

Identity matters in science, technology, engineering, mathematics, and medicine (STEMM) because it can affect an individual's long-term sense of belonging, which may in turn affect their persistence in STEMM. Early K-12 science classes often teach students about the foundational discoveries of the field, which have been predominately made, or at least published, by White men. This homogeneity can leave underrepresented individuals in STEMM feeling isolated, and underrepresented K-12 students may feel as though they cannot enter STEMM fields. This study aimed to examine these feelings of inclusivity in STEMM through an interactive workshop that asked middle schoolers to identify scientists from images of individuals with various racial and gender identities. We found that a plurality of students had a positive experience discussing diversity in science and recognizing underrepresented individuals as scientists.NEW & NOTEWORTHY We observed positive sentiments from middle school students following a workshop that showcased diversity in science. This workshop uniquely encourages students to recognize that physiologists and scientists today are much more diverse than textbooks typically demonstrate and can be adapted for middle schoolers, high schoolers, and college students.

A workshop on mitochondria for students to improve understanding of science and hypothesis forming.

There remains a clear deficiency in recruiting middle school students in science, technology, engineering, mathematics, and medicine fields, especially for those students entering physiology from underrepresented backgrounds. A large part of this may be arising from a disconnect between how science is typically practiced at a collegiate and K-12 level. Here, we have envisioned mitochondria and their diverse subcellular structures as an involver for middle school students. We present the framework for a workshop that familiarizes students with mitochondria, employing three-dimensional visual-spatial learning and real-time critical thinking and hypothesis forming. This workshop had the goal of familiarizing middle school students with the unique challenges the field currently faces and better understanding the actuality of being a scientist through critical analysis including hypothesis forming. Findings show that middle school students responded positively to the program and felt as though they had a better understanding of mitochondria. Future implications for hands-on programs to involve underrepresented students in science are discussed, as well as potential considerations to adapt it for high school and undergraduate students.NEW & NOTEWORTHY Here we employ a workshop that utilizes blended and tactile learning to teach middle schoolers about mitochondrial structure. By creating an approachable and fun workshop that can be utilized for middle school students, we seek to encourage them to join a career in physiology.

Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses.

Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.

Effects of increased body mass index on employment status: a Mendelian randomisation study.

BACKGROUND: The obesity epidemic may have substantial implications for the global workforce, including causal effects on employment, but clear evidence is lacking. Obesity may prevent people from being in paid work through poor health or through social discrimination. We studied genetic variants robustly associated with body mass index (BMI) to investigate its causal effects on employment. DATASET/METHODS: White UK ethnicity participants of working age (men 40-64 years, women 40-59 years), with suitable genetic data were selected in the UK Biobank study (N = 230,791). Employment status was categorised in two ways: first, contrasting being in paid employment with any other status; and second, contrasting being in paid employment with sickness/disability, unemployment, early retirement and caring for home/family. Socioeconomic indicators also investigated were hours worked, household income, educational attainment and Townsend deprivation index (TDI). We conducted observational and two-sample Mendelian randomisation (MR) analyses to investigate the effect of increased BMI on employment-related outcomes. RESULTS: Regressions showed BMI associated with all the employment-related outcomes investigated. MR analyses provided evidence for higher BMI causing increased risk of sickness/disability (OR 1.08, 95% CI 1.04, 1.11, per 1 Kg/m2 BMI increase) and decreased caring for home/family (OR 0.96, 95% CI 0.93, 0.99), higher TDI (Beta 0.038, 95% CI 0.018, 0.059), and lower household income (OR 0.98, 95% CI 0.96, 0.99). In contrast, MR provided evidence for no causal effect of BMI on unemployment, early retirement, non-employment, hours worked or educational attainment. There was little evidence for causal effects differing by sex or age. Robustness tests yielded consistent results. DISCUSSION: BMI appears to exert a causal effect on employment status, largely by affecting an individual's health rather than through increased unemployment arising from social discrimination. The obesity epidemic may be contributing to increased worklessness and therefore could impose a substantial societal burden.

Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees.

Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current.

Salt stress in the renal tubules is linked to TAL-specific expression of uromodulin and an upregulation of heat shock genes.

Previously, our comprehensive cardiovascular characterization study validated Uromodulin as a blood pressure gene. Uromodulin is a glycoprotein exclusively synthesized at the thick ascending limb of the loop of Henle and is encoded by the Umod gene. Umod-/- mice have significantly lower blood pressure than Umod+/+ mice, are resistant to salt-induced changes in blood pressure, and show a leftward shift in pressure-natriuresis curves reflecting changes of sodium reabsorption. Salt stress triggers transcription factors and genes that alter renal sodium reabsorption. To date there are no studies on renal transcriptome responses to salt stress. Here we aimed use RNA-Seq to delineate salt stress pathways in tubules isolated from Umod+/+ mice (a model of sodium retention) and Umod-/- mice (a model of sodium depletion) ± 300 mosmol sodium chloride ( n = 3 per group). In response to salt stress, the tubules of Umod+/+ mice displayed an upregulation of heat shock transcripts. The greatest changes occurred in the expression of: Hspa1a (Log2 fold change 4.35, P = 2.48 e-12) and Hspa1b (Log2 fold change 4.05, P = 2.48 e-12). This response was absent in tubules of Umod-/- mice. Interestingly, seven of the genes discordantly expressed in the Umod-/- tubules were electrolyte transporters. Our results are the first to show that salt stress in renal tubules alters the transcriptome, increasing the expression of heat shock genes. This direction of effect in Umod+/+ tubules suggest the difference is due to the presence of Umod facilitating greater sodium entry into the tubule cell reflecting a specific response to salt stress.

Reconstructing Native American population history.

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call 'First American'. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

Sacral agenesis: a pilot whole exome sequencing and copy number study.

BACKGROUND: Caudal regression syndrome (CRS) or sacral agenesis is a rare congenital disorder characterized by a constellation of congenital caudal anomalies affecting the caudal spine and spinal cord, the hindgut, the urogenital system, and the lower limbs. CRS is a complex condition, attributed to an abnormal development of the caudal mesoderm, likely caused by the effect of interacting genetic and environmental factors. A well-known risk factor is maternal type 1 diabetes. METHOD: Whole exome sequencing and copy number variation (CNV) analyses were conducted on 4 Caucasian trios to identify de novo and inherited rare mutations. RESULTS: In this pilot study, exome sequencing and copy number variation (CNV) analyses implicate a number of candidate genes, including SPTBN5, MORN1, ZNF330, CLTCL1 and PDZD2. De novo mutations were found in SPTBN5, MORN1 and ZNF330 and inherited predicted damaging mutations in PDZD2 (homozygous) and CLTCL1 (compound heterozygous). Importantly, predicted damaging mutations in PTEN (heterozygous), in its direct regulator GLTSCR2 (compound heterozygous) and in VANGL1 (heterozygous) were identified. These genes had previously been linked with the CRS phenotype. Two CNV deletions, one de novo (chr3q13.13) and one homozygous (chr8p23.2), were detected in one of our CRS patients. These deletions overlapped with CNVs previously reported in patients with similar phenotype. CONCLUSION: Despite the genetic diversity and the complexity of the phenotype, this pilot study identified genetic features common across CRS patients.

Local True Discovery Rate Weighted Polygenic Scores Using GWAS Summary Data.

A polygenic score is commonly derived using genome-wide genotype data to summarize the genetic contribution to a particular disease at the individual level. Usually it is constructed as a linear combination of SNP genotype weighted by the SNP-wise regression coefficient of the SNP to the phenotype using SNPs with p values smaller than a particular threshold. Commonly a range of thresholds are used which can pose problems with multiple comparisons as well as over-fitting. Here, an alternative weighting scheme is proposed, making use of the local true discovery rate, estimated from summary statistics. Two methods of estimation are proposed-maximum likelihood and kernel density estimation. Simulation studies using real and artificial data suggest this new weighting scheme is highly comparable with standard polygenic scores using the best possible p value threshold in prediction, even though this threshold is not normally known in practice.

Partitioning the heritability of Tourette syndrome and obsessive compulsive disorder reveals differences in genetic architecture.

The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.

The emerging molecular architecture of schizophrenia, polygenic risk scores and the clinical implications for GxE research.

Schizophrenia is a devastating mental disorder. The level of risk in the general population is sustained by the persistence of social, environmental and biological factors, as well as their interactions. Socio-environmental risk factors for schizophrenia are well established and robust. The same can belatedly be said of genetic risk factors for the disorder. Recent progress in schizophrenia genetics is primarily fuelled by genome-wide association, which is able to leverage substantial proportions of additional explained variance previously classified as 'missing'. Here, we provide an outline of the emerging genetic landscape of schizophrenia and demonstrate how this knowledge can be turned into a simple empirical measure of genetic risk, known as a polygenic risk score. We highlight the statistical framework used to assess the clinical potential of the new score and finally, draw relevance to and discuss the clinical implications for the study of gene-environment interaction.

Comparing Anxiety and Depression in Information Technology Workers with Others in Employment: A UK Biobank Cohort Study.

OBJECTIVES: Despite reported psychological hazards of information technology (IT) work, studies of diagnosed mental health conditions in IT workers are lacking. We investigated self-reported mental health outcomes and incident anxiety/depression in IT workers compared to others in employment in a large population-based cohort. METHODS: We evaluated self-reported mental health outcomes in the UK Biobank cohort and incident diagnosed anxiety/depression through health record linkage. We used logistic regression and Cox models to compare the risks of prevalent and incident anxiety/depression among IT workers with all other employed participants. Furthermore, we compared outcomes within IT worker subgroups, and between these subgroups and other similar occupations within their major Standard Occupational Classification (SOC) group. RESULTS: Of 112 399 participants analyzed, 4093 (3.6%) were IT workers. At baseline, IT workers had a reduced odds (OR = 0.66, 95%CI: 0.52-0.85) of anxiety/depression symptoms and were less likely (OR = 0.87, 95%CI: 0.83-0.91) to have ever attended their GP for anxiety/depression, compared to all other employed participants, after adjustment for confounders. The IT technician subgroup were more likely (OR = 1.22, 95%CI: 1.07-1.40) to have previously seen their GP or a psychiatrist (OR = 1.31, 95%CI: 1.06-1.62) for anxiety/depression than their SOC counterparts. IT workers had lower incident anxiety/depression (HR = 0.84, 95%CI 0.77-0.93) compared to all other employed participants, after adjustment for confounders. CONCLUSIONS: Our findings from this, the first longitudinal study of IT worker mental health, set the benchmark in our understanding of the mental health of this growing workforce and identification of high-risk groups. This will have important implications for targeting mental health workplace interventions.

Effects of depression on employment and social outcomes: a Mendelian randomisation study.

BACKGROUND: Depression is associated with socioeconomic disadvantage. However, whether and how depression exerts a causal effect on employment remains unclear. We used Mendelian randomisation (MR) to investigate whether depression affects employment and related outcomes in the UK Biobank dataset. METHODS: We selected 227 242 working-age participants (40-64 in men, 40-59 years for women) of white British ethnicity/ancestry with suitable genetic data in the UK Biobank study. We used 30 independent genetic variants associated with depression as instruments. We conducted observational and two-sample MR analyses. Outcomes were employment status (employed vs not, and employed vs sickness/disability, unemployment, retirement or caring for home/family); weekly hours worked (among employed); Townsend Deprivation Index; highest educational attainment; and household income. RESULTS: People who had experienced depression had higher odds of non-employment, sickness/disability, unemployment, caring for home/family and early retirement. Depression was associated with reduced weekly hours worked, lower household income and lower educational attainment, and increased deprivation. MR analyses suggested depression liability caused increased non-employment (OR 1.16, 95% CI 1.06 to 1.26) and sickness/disability (OR 1.56, 95% CI 1.34 to 1.82), but was not causal for caring for home/family, early retirement or unemployment. There was little evidence from MR that depression affected weekly hours worked, educational attainment, household income or deprivation. CONCLUSIONS: Depression liability appears to cause increased non-employment, particularly by increasing disability. There was little evidence of depression affecting early retirement, hours worked or household income, but power was low. Effective treatment of depression might have important economic benefits to individuals and society.

Impact of Brazil's Bolsa Família Programme on cardiovascular and all-cause mortality: a natural experiment study using the 100 Million Brazilian Cohort.

BACKGROUND: Cardiovascular disease (CVD) has a disproportionate effect on mortality among the poorest people. We assessed the impact on CVD and all-cause mortality of the world's largest conditional cash transfer, Brazil's Bolsa Família Programme (BFP). METHODS: We linked administrative data from the 100 Million Brazilian Cohort with BFP receipt and national mortality data. We followed individuals who applied for BFP between 1 January 2011 and 31 December 2015, until 31 December 2015. We used marginal structural models to estimate the effect of BFP on all-age and premature (30-69 years) CVD and all-cause mortality. We conducted stratified analyses by levels of material deprivation and access to healthcare. We checked the robustness of our findings by restricting the analysis to municipalities with better mortality data and by using alternative statistical methods. RESULTS: We studied 17 981 582 individuals, of whom 4 855 324 were aged 30-69 years. Three-quarters (76.2%) received BFP, with a mean follow-up post-award of 2.6 years. We detected 106 807 deaths by all causes, of which 60 893 were premature; and 23 389 CVD deaths, of which 15 292 were premature. BFP was associated with reductions in premature all-cause mortality [hazard ratio (HR) = 0.96, 95% CI = 0.94-0.98], premature CVD (HR = 0.96, 95% CI = 0.92-1.00) and all-age CVD (HR = 0.96, 95% CI = 0.93-1.00) but not all-age all-cause mortality (HR = 1.00, 95% CI = 0.98-1.02). In stratified and robustness analyses, BFP was consistently associated with mortality reductions for individuals living in the two most deprived quintiles. CONCLUSIONS: BFP appears to have a small to null effect on premature CVD and all-cause mortality in the short term; the long-term impact remains unknown.

Software for generating liability distributions for pedigrees conditional on their observed disease states and covariates.

For many multifactorial diseases, aetiology is poorly understood. A major research aim is the identification of disease predictors (environmental, biological, and genetic markers). In order to achieve this, a two-stage approach is proposed. The initial or synthesis stage combines observed pedigree data with previous genetic epidemiological research findings, to produce estimates of pedigree members' disease risk and predictions of their disease liability. A further analysis stage uses the latter as inputs to look for associations with potential disease markers. The incorporation of previous research findings into an analysis should lead to power gains. It also allows separate predictions for environmental and genetic liabilities to be generated. This should increase power for detecting disease predictors that are environmental or genetic in nature. Finally, the approach brings pragmatic benefits in terms of data reduction and synthesis, improving comprehensibility, and facilitating the use of existing statistical genetics tools. In this article we present a statistical model and Gibbs sampling approach to generate liability predictions for multifactorial disease for the synthesis stage. We have implemented the approach in a software program. We apply this program to a specimen disease pedigree, and discuss the results produced, comparing its results with those generated under a more naïve model. We also detail simulation studies that validate the software's operation.

Mental health and health behaviours before and during the initial phase of the COVID-19 lockdown: longitudinal analyses of the UK Household Longitudinal Study.

BACKGROUND: There are concerns that COVID-19 mitigation measures, including the 'lockdown', may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups. METHODS: Repeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of over 27,000 adults (aged 18+) interviewed in four survey waves between 2015 and 2020. A total of 9748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity. RESULTS: Psychological distress increased 1 month into lockdown with the prevalence rising from 19.4% (95% CI 18.7% to 20.1%) in 2017-2019 to 30.6% (95% CI 29.1% to 32.3%) in April 2020 (RR=1.3, 95% CI 1.2 to 1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI 0.6 to 1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI 1.3 to 1.5), as did binge drinking (RR=1.5, 95% CI 1.3 to 1.7). CONCLUSIONS: Psychological distress increased 1 month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate negative impacts on health.

Clinical burden, risk factor impact and outcomes following myocardial infarction and stroke: A 25-year individual patient level linkage study.

BACKGROUND: Understanding trends in the incidence and outcomes of myocardial infarction and stroke, and how these are influenced by changes in cardiovascular risk factors can inform health policy and healthcare provision. METHODS: We identified all patients 30 years or older with myocardial infarction or stroke in Scotland. Risk factor levels were determined from national health surveys. Incidence, potential impact fractions and burden attributable to risk factor changes were calculated. Risk of subsequent fatal and non-fatal events (myocardial infarction, stroke, bleeding and heart failure hospitalization) were calculated with multi-state models. FINDINGS: From 1990 to 2014, there were 372,873 (71±13 years) myocardial infarctions and 290,927 (74±13 years) ischemic or hemorrhagic strokes. Age-standardized incidence per 100,000 fell from 1,069 (95% confidence interval, 1,024-1,116) to 276 (263-290) for myocardial infarction and from 608 (581-636) to 188 (178-197) for ischemic stroke. Systolic blood pressure, smoking and cholesterol decreased, but body-mass index increased, and diabetes prevalence doubled. Changes in risk factors accounted for a 74% (57-91%) reduction in myocardial infarction and 68% (55-83%) reduction in ischemic stroke. Following myocardial infarction, the risk of death decreased (30% to 20%), but non-fatal events increased (20% to 24%) whereas the risk of both death (47% to 34%) and non-fatal events (22% to 17%) decreased following stroke. INTERPRETATION: Over the last 25 years, substantial reductions in myocardial infarction and ischemic stroke incidence are attributable to major shifts in risk factor levels. Deaths following the index event decreased for both myocardial infarction and stroke, but rates remained substantially higher for stroke. FUNDING: British heart foundation.

The causal effects of health conditions and risk factors on social and socioeconomic outcomes: Mendelian randomization in UK Biobank.

BACKGROUND: We aimed to estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy makers and decision makers allocate resources efficiently and effectively. METHODS: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors [alcohol intake, body mass index (BMI), cholesterol, systolic blood pressure, smoking] on 19 social and socioeconomic outcomes in 336 997 men and women of White British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation [measured by the Townsend deprivation index (TDI)], degree-level education, happiness, loneliness and 13 other social and socioeconomic outcomes. RESULTS: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income [mean difference = -£22 838, 95% confidence interval (CI): -£31 354 to -£14 321] and the chance of owning accommodation [absolute percentage change (APC) = -20.8%, 95% CI: -28.2% to -13.4%], of being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%) and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. CONCLUSIONS: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects.

Suicidal ideation during treatment of depression with escitalopram and nortriptyline in genome-based therapeutic drugs for depression (GENDEP): a clinical trial.

BACKGROUND: Suicidal thoughts and behaviours during antidepressant treatment, especially during the first weeks of treatment, have prompted warnings by regulatory bodies. The aim of the present study is to investigate the course and predictors of emergence and worsening of suicidal ideation during tricyclic antidepressant and serotonin reuptake inhibitor treatment. METHODS: In a multicentre part-randomised open-label study, 811 adult patients with moderate to severe unipolar depression were allocated to flexible dosage of escitalopram or nortriptyline for 12 weeks. The suicidality items of three standard measures were integrated in a suicidal ideation score. Increases in this score were classified as treatment emergent suicidal ideation (TESI) or treatment worsening suicidal ideation (TWOSI) according to the absence or presence of suicidal ideation at baseline. RESULTS: Suicidal ideation decreased during antidepressant treatment. Rates of TESI and TWOSI peaked in the fifth week. Severity of depression predicted TESI and TWOSI. In men, nortriptyline was associated with a 9.8-fold and 2.4-fold increase in TESI and TWOSI compared to escitalopram, respectively. Retirement and history of suicide attempts predicted TWOSI. CONCLUSION: Increases in suicidal ideation were associated with depression severity and decreased during antidepressant treatment. In men, treatment with escitalopram is associated with lower risk of suicidal ideation compared to nortriptyline. Clinicians should remain alert to suicidal ideation beyond the initial weeks of antidepressant treatment. TRIAL REGISTRATION: EudraCT (No.2004-001723-38) and ISRCTN (No. 03693000).

Gene Variants at Loci Related to Blood Pressure Account for Variation in Response to Antihypertensive Drugs Between Black and White Individuals.

Selection of antihypertensive treatment according to self-defined ethnicity is recommended by some guidelines but might be better guided by individual genotype rather than ethnicity or race. We compared the extent to which variation in blood pressure response across different ethnicities may be explained by genetic factors: genetically defined ancestry and gene variants at loci known to be associated with blood pressure. We analyzed data from 5 trials in which genotyping had been performed (n=4696) and in which treatment responses to ß-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blocker, thiazide or thiazide-like diuretic and calcium channel blocker were available. Genetically defined ancestry for proportion of African ancestry was computed using the 1000 genomes population database as a reference. Differences in response to the thiazide diuretic hydrochlorothiazide, the ß-blockers atenolol and metoprolol, the angiotensin-converting enzyme inhibitor lisinopril, and the angiotensin receptor blocker candesartan were more closely associated to genetically defined ancestry than self-defined ethnicity in admixed subjects. A relatively small number of gene variants related to loci associated with drug-signaling pathways (KCNK3, SULT1C3, AMH, PDE3A, PLCE1, PRKAG2) with large effect size (-3.5 to +3.5 mm Hg difference in response per allele) and differing allele frequencies in black versus white individuals explained a large proportion of the difference in response to candesartan and hydrochlorothiazide between these groups. These findings suggest that a genomic precision medicine approach can be used to individualize antihypertensive treatment within and across populations without recourse to surrogates of genetic structure such as self-defined ethnicity.