Cluster analysis identifies unmet healthcare needs among patients with rheumatoid arthritis

Objective: To identify the patterns of healthcare resource utilization and unmet needs of persistent disease activity, pain, and physical disability in rheumatoid arthritis (RA) by cluster analysis. Method: Patients attending the Jyvaskyla Central Hospital rheumatology unit, Finland, were, from 2007, prospectively enrolled in a clinical database. We identified all RA patients in 2010-2014 and combined their individual-level data with well-recorded administrative data on all public healthcare contacts in fiscal year 2014. We ran agglomerative hierarchical clustering (Ward's method), with 28-joint Disease Activity Score with three variables, Health Assessment Questionnaire index, pain (visual analogue scale 0-100), and total annual health service-related direct costs (euro) as clustering variables. Results: Complete-case analysis of 939 patients derived four clusters. Cluster C1 (remission and low costs, 550 patients) comprised relatively young patients with low costs, low disease activity, and minimal disability. C2 (chronic pain, disability, and fatigue, 269 patients) included those with the highest pain and fatigue levels, and disability was fairly common. C3 (inflammation, 97 patients) had rather high mean costs and the highest average disease activity, but lower average levels of pain and less disability than C2, highlighting the impact of effective treatment. C4 (comorbidities and high costs, 23 patients) was characterized by exceptionally high costs incurred by comorbidities. Conclusions: The majority of RA patients had favourable outcomes and low costs. However, a large group of patients was distinguished by chronic pain, disability, and fatigue not unambiguously linked to disease activity. The highest healthcare costs were linked to high disease activity or comorbidities.Peer reviewe

Informed consent procedures in patients with an acute inability to provide informed consent : Policy and practice in the CENTER-TBI study

Purpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in European and national legislation, which allows procedural variation and bias. We aimed to quantify variations in informed consent policy and practice. Methods: Variation was explored in the CENTER-TBI study. Policies were reported by using a questionnaire and national legislation. Data on used informed consent procedures were available for 4498 patients from 57 centres across 17 European countries. Results: Variation in the use of informed consent procedures was found between and within EU member states. Proxy informed consent (N = 1377;64%) was the most frequently used type of consent in the ICU, followed by patient informed consent (N 426;20%) and deferred consent (N 334;16%). Deferred consent was only actively used in 15 centres (26%), although it was considered valid in 47 centres (82%). Conclusions: Alternatives to patient consent are essential for TBI research. While there seems to be concordance amongst national legislations, there is regional variability in institutional practices with respect to the use of different informed consent procedures. Variation could be caused by several reasons, including inconsistencies in clear legislation or knowledge of such legislation amongst researchers. (C) 2020 Published by Elsevier Inc.Peer reviewe

Genetic risk factors have a substantial impact on healthy life years

The impact of genetic variation on overall disease burden has not been comprehensively evaluated. We introduce an approach to estimate the effect of genetic risk factors on disability-adjusted life years (DALYs; 'lost healthy life years'). We use genetic information from 735,748 individuals and consider 80 diseases. Rare variants had the highest effect on DALYs at the individual level. Among common variants, rs3798220 (LPA) had the strongest individual-level effect, with 1.18 DALYs from carrying 1 versus 0 copies. Being in the top 10% versus the bottom 90% of a polygenic score for multisite chronic pain had an effect of 3.63 DALYs. Some common variants had a population-level effect comparable to modifiable risk factors such as high sodium intake and low physical activity. Attributable DALYs vary between males and females for some genetic exposures. Genetic risk factors can explain a sizable number of healthy life years lost both at the individual and population level.Peer reviewe

Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine's polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100-12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of 'pleiotropic' variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.Peer reviewe

Exome sequencing of Finnish isolates enhances rare-variant association power.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power

Genome-wide risk prediction of common diseases across ancestries in one million people

Peer reviewe

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve

Risk of nontyphoidal Salmonella bacteraemia in African children is modified by STAT4

Nontyphoidal Salmonella (NTS) is a major cause of bacteraemia in Africa. The disease typically affects HIV-infected individuals and young children, causing substantial morbidity and mortality. Here we present a genome-wide association study (180 cases, 2677 controls) and replication analysis of NTS bacteraemia in Kenyan and Malawian children. We identify a locus in STAT4, rs13390936, associated with NTS bacteraemia. rs13390936 is a context-specific expression quantitative trait locus for STAT4 RNA expression, and individuals carrying the NTS-risk genotype demonstrate decreased interferon-gamma (IFN gamma) production in stimulated natural killer cells, and decreased circulating IFN gamma concentrations during acute NTS bacteraemia. The NTS-risk allele at rs13390936 is associated with protection against a range of autoimmune diseases. These data implicate interleukin-12-dependent IFN gamma-mediated immunity as a determinant of invasive NTS disease in African children, and highlight the shared genetic architecture of infectious and autoimmune disease.Peer reviewe

Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke

Genetic factors have been implicated in stroke risk but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) in ischemic stroke and its subtypes in 3,548 cases and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 cases and 6,281 controls. We replicated reported associations between variants close to PITX2 and ZFHX3 with cardioembolic stroke, and a 9p21 locus with large vessel stroke. We identified a novel association for a SNP within the histone deacetylase 9(HDAC9) gene on chromosome 7p21.1 which was associated with large vessel stroke including additional replication in a further 735 cases and 28583 controls (rs11984041, combined P = 1.87×10−11, OR=1.42 (95% CI) 1.28-1.57). All four loci exhibit evidence for heterogeneity of effect across the stroke subtypes, with some, and possibly all, affecting risk for only one subtype. This suggests differing genetic architectures for different stroke subtypes

Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis.

Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of human genetics, patient metabolite and cytokine measurements, and testing in a mouse model demonstrate that the methionine salvage pathway is a regulator of sepsis that can accurately predict prognosis in patients. Pathway-based genome-wide association analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide polymorphisms near the components of the methionine salvage pathway. Measurement of the pathway's substrate, methylthioadenosine (MTA), in two cohorts of sepsis patients demonstrated increased plasma MTA in nonsurvivors. Plasma MTA was correlated with levels of inflammatory cytokines, indicating that elevated MTA marks a subset of patients with excessive inflammation. A machine-learning model combining MTA and other variables yielded approximately 80% accuracy (area under the curve) in predicting death. Furthermore, mice infected with Salmonella had prolonged survival when MTA was administered before infection, suggesting that manipulating MTA levels could regulate the severity of the inflammatory response. Our results demonstrate how combining genetic data, biomolecule measurements, and animal models can shape our understanding of disease and lead to new biomarkers for patient stratification and potential therapeutic targeting