Discovering common genetic variants for hypertension using an extreme case-control strategy

Hypertension is a common, highly heritable trait of complex aetiology. Multiple environmental and lifestyle factors contribute to blood pressure variation. Hence the study of hypertension causality is not straightforward. Genetic linkage studies have implicated a number of loci involved in blood pressure regulation and the development of hypertension. Candidate gene association studies, however, have not reported any reproducible associations. Early genome-wide association studies (GWAS) showed remarkable success in identifying validated common variants associated with common diseases such as coronary artery disease and type 1 diabetes. However, the first GWAS of hypertension showed little success. This was largely because of a lack of statistical power and insufficient genomic coverage. Furthermore, it is widely believed that the failure of one GWAS of hypertension was partly due to misclassification of controls that were not phenotyped for blood pressure. Subsequently, two large international consortia-run GWAS of blood pressure as a quantitative trait produced tangible results. The current study is a GWAS of hypertension using an extreme case-control design. It employed intensive phenotyping and extreme case-control definitions to select a sample of individuals from a restricted geographical area of relative homogeneity. The aim was to reduce misclassification bias and increase the likelihood of detecting any genetic effects. Cases were sampled from the Nordic Diltiazem study, and defined as individuals younger than 60 years with at least two consecutive measurements of systolic blood pressure (SBP) ≥ 160 mmHg or diastolic blood pressure (DBP) ≥ 100 mmHg. Controls were sampled from the prospective Malmö Diet and Cancer Study, and defined as individuals aged at least 50 years with SBP ≤ 120 mmHg and DBP ≤ 80 mmHg with no evidence of cardiovascular disease during ten years of follow-up. The groups represent, respectively, the upper 1.7% and lower 9.2% of the Swedish blood pressure distribution. Comparison of groups from the extreme tails of distribution increased statistical power by inflating observed effect sizes. With genome-wide SNP coverage we were able to adjust for population stratification using principal components analysis. Following quality control exclusions, a final set of 521,220 single nucleotide polymorphisms was available for analysis in 1,621 cases and 1,699 controls. Seventeen SNPs were associated with hypertension at a P < 1 × 10-5 threshold of significance, of which three attained genome-wide significance, defined as P < 5 × 10-7. The top hit, rs13333226, underwent a two stage validation process in a total of 14 independent cohorts. The combined odds ratio for the discovery cohort and all replication cohorts meta-analysed was 0.87 (95% CI 0.84 – 0.91, P = 3.67 × 10-11) with the minor G allele associated with a lower risk of hypertension. In total 21,466 cases and 18,240 controls were included. After adjustment for age, age2, sex, and BMI, and when the discovery cohort was excluded from analysis, the association remained significant. Estimated glomerular filtration rate (eGFR), a measure of kidney function, was available in seven of the cohorts. When the analysis was repeated with adjustment for eGFR the effect was marginally strengthened. rs13333226 is located in close proximity, at -1617 base pairs, to the uromodulin (UMOD) transcription start site. UMOD encodes uromodulin, also known as the Tamm-Horsfall protein. Uromodulin is produced predominantly in the thick ascending limb of the loop of Henle and is the most abundant protein in urine. Its function is unclear; however, variants in UMOD have been associated with chronic kidney disease. Clinical functional studies were conducted in three separate populations. The minor G allele of rs13333226 (associated with a lower risk of hypertension) was associated with lower urinary uromodulin excretion. Furthermore, in one sample following a low salt diet urinary uromodulin excretion was significantly lower in the presence of the G allele, whereas after a high salt diet genotype was no longer associated with urinary uromodulin. If this were verified, this would entail a gene-environment interaction. Our combined results suggest that UMOD may have a role in regulating blood pressure, possibly through an effect on sodium homeostasis. There is ample evidence of a strong, graded relationship between blood pressure and subsequent renal disease. Hence the current finding is biologically plausible. Information on kidney disease was not available for the discovery samples so this could not be explored. However, the association between rs13333226 and hypertension was not substantively altered by adjustment for eGFR in the seven validation cohorts in which it was recorded, suggesting that it is independent of renal function. In conclusion, we have performed a GWAS of hypertension using an extreme case-control design. The most significant hit was validated in a meta-analysis of the discovery sample and 14 additional cohorts. Moreover, functional studies showed a relationship between genotype and urinary protein excretion. Overall, we demonstrate that with careful methodological planning and phenotyping it is possible to generate replicable hypertension GWAS results in a relatively small sample size

Genome-Wide Association Studies of Hypertension: Light at the End of the Tunnel

Despite its significant genetic component, the study of hypertension by genome-wide association presents more challenges than other common complex diseases. Its high prevalence, heterogeneity, and somewhat unclear definition are the challenges that need to be overcome on one hand. On the other hand, there are issues of small effect sizes and pleiotropism that are not specific to hypertension alone but nonetheless magnify the problems of genetic dissection when coupled with phenotypic misclassification. We discuss issues of study design and summarise published genome-wide association studies (GWASs) of hypertension and blood pressure. With careful study design and analysis success is possible, as demonstrated by the recent large-scale studies. Following these, there is still further scope to advance the field through high fidelity phenotyping and deep sequencing

Effects of Amount of Information on Overconfidence

Title: Effects of amount of information on overconfidenceAuthors: Tsai, Claire; Klayman, Joshua; Hastie, ReidAffiliation: The University of ChicagoAbstract: When a person makes a judgment based on evidence and assesses confidence in that judgment, what is the effect of providing more judgment-relevant information? Findings by Oskamp (1965) and by Slovic and Corrigan (1977) suggest that more information leads to increasing overconfidence. , We replicate the finding that receiving more information leads judges to increase their confidence even when their predictive accuracy does not improve. We identify some likely candidates for cues people use to judge confidence that do not correlate well with actual accuracy

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Despite its significant genetic component, the study of hypertension by genome-wide association presents more challenges than other common complex diseases. Its high prevalence, heterogeneity, and somewhat unclear definition are the challenges that need to be overcome on one hand. On the other hand, there are issues of small effect sizes and pleiotropism that are not specific to hypertension alone but nonetheless magnify the problems of genetic dissection when coupled with phenotypic misclassification. We discuss issues of study design and summarise published genome-wide association studies (GWASs) of hypertension and blood pressure. With careful study design and analysis success is possible, as demonstrated by the recent large-scale studies. Following these, there is still further scope to advance the field through high fidelity phenotyping and deep sequencing

Co-induction of cyclooxyenase-2 and early growth response gene (Egr-1) in spinal cord in a clinical model of persistent inflammation and hyperalgesia

BackgroundThis study characterised the effects of persistent peripheral inflammation of the foot on pain and spinal cord expression of cyclooxygenase-1 and -2 (COX-1 and COX-2) and early growth response gene 1 (Egr-1), known markers of neuronal plasticity, in a clinical model of naturally-occurring inflammatory disease and hyperalgesia in sheep ('footrot'), before and after routine treatment (parenteral treatment with antibiotics and antiseptic footbathing). The temporal pattern of expression of COX-1, COX-2 and Egr-1 mRNA and protein were analysed using real-time PCR and Western blotting. ResultsAnimals affected with persistent peripheral inflammation displayed significant hyperalgesia and lameness (a proxy indicator of spontaneous pain) restricted to the inflamed limb. Hyperalgesia and lameness were significantly attenuated 1 day after treatment, and resolved further by day 7 and day 3, respectively. COX-2 but not COX-1, protein expression was up-regulated in spinal cord from lame animals on day 0, before treatment. Following treatment and attenuation of pain behaviours, levels of COX-2 returned to control levels. Significant induction of Egr-1 mRNA and protein were observed in spinal cord from lame animals. Three days after treatment, levels of Egr-1 mRNA returned to control levels, however, Egr-1 protein remained elevated. ConclusionElevated levels of spinal COX-2 and Egr-1 protein correlate with the presence of pain and hyperalgesia, and may underlie persistent pain, although a direct causal link has still to be established. Understanding the temporal pattern of expression of key mediators in clinical pain states may lead to better strategies to manage pai

Association between walking pace and stroke incidence: findings from the UK Biobank prospective cohort study

Background and Purpose— Stroke incidence in younger and middle-aged people is growing. Despite this, its associations in this subset of the stroke population are unknown, and prevention strategies are not tailored to meet their needs. This study examined the association between self-reported walking pace and incident stroke. Methods— Data from the UK Biobank were used in a prospective population-based study. Three hundred and sixty-three thousand, one hundred and thirty-seven participants aged 37 to 73 years (52% women) were recruited. The associations of self-reported walking pace with stroke incidence over follow-up were investigated using Cox proportional-hazard models. Results— Among 363,137 participants, 2705 (0.7%) participants developed a fatal or nonfatal stroke event over the mean follow-up period of 6.1 years (interquartile range, 5.4–6.7). Slow walking pace was associated with a higher hazard for stroke incidence (hazard ratio [HR], 1.45 [95% CI, 1.26–1.66]; P&lt;0.0001). Stroke incidence was not associated with walking pace among people &lt;65 years of age. However, slow walking pace was associated with a higher risk of stroke among participants aged ≥65 years (HR, 1.42 [95% CI, 1.17–1.72]; P&lt;0.0001). A higher risk for stroke was observed on those with middle (HR, 1.28 [95% CI, 1.01–1.63]; P=0.039) and higher (HR, 1.29 [95% CI, 1.05–1.69]; P=0.012) deprivation levels but not in the least deprived individuals. Similarly, overweight (HR, 1.30 [95% CI, 1.04–1.63]; P=0.019) and obese (HR, 1.33 [95% CI, 1.09–1.63]; P=0.004) but not normal-weight individuals had a higher risk of stroke incidence. Conclusions— Slow walking pace was associated with a higher risk of stroke among participants over 64 years of age in this population-based cohort study. The addition of the measurement of self-reported walking pace to primary care or public health clinical consultations may be a useful screening tool for stroke risk

Long Covid stigma: estimating burden and validating scale in a UK-based sample

Background Stigma can be experienced as perceived or actual disqualification from social and institutional acceptance on the basis of one or more physical, behavioural or other attributes deemed to be undesirable. Long Covid is a predominantly multisystem condition that occurs in people with a history of SARSCoV2 infection, often resulting in functional disability. This study aimed to develop and validate a Long Covid Stigma Scale (LCSS); and to quantify the burden of Long Covid stigma. Methods Data from the follow-up of a co-produced community-based Long Covid online survey using convenience non-probability sampling was used. Thirteen questions on stigma were designed to develop the LCSS capturing three domains-enacted (overt experiences of discrimination), internalised (internalising negative associations with Long Covid and accepting them as self-applicable) and anticipated (expectation of bias/poor treatment by others) stigma. Confirmatory factor analysis tested whether LCSS consisted of the three hypothesised domains. Model fit was assessed and prevalence was calculated. Results 966 UK-based participants responded (888 for stigma questions), with mean age 48 years (SD: 10.7) and 85% female. Factor loadings for enacted stigma were 0.70-0.86, internalised 0.75-0.84, anticipated 0.58-0.87, and model fit was good. The prevalence of experiencing stigma at least 'sometimes' and 'often/always' was 95% and 76% respectively. Anticipated and internalised stigma were more frequently experienced than enacted stigma. Those who reported having a clinical diagnosis of Long Covid had higher stigma prevalence than those without. Conclusion This study establishes a scale to measure Long Covid stigma and highlights common experiences of stigma in people living with Long Covid

Genome maps across 26 human populations reveal population-specific patterns of structural variation.

Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (&gt;2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort

Background: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. Methods and findings: We studied data from UK Biobank (428,199 participants; aged 37–73; recruited 2006–2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96–1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28–1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12–1.46) and 1.77 (1.46–2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09–3.78); 2.79 (2.00–3.90); 2.66 (1.88–3.76); 2.13 (1.46–3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. Conclusions: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19