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This trial compared genotype-guided dosing with standard dosing in patients with atrial fibrillation or venous thromboembolism initiating warfarin anticoagulation. Genotype-guided dosing was associated with a higher percentage of time in the therapeutic INR range of 2.0 to 3.0. Warfarin has proved to be effective in the management of thromboembolic disease 1 but has a narrow therapeutic index, with wide variation among patients in the daily doses required; this variation can lead to either excessive or insufficient anticoagulation. 2 An increase in the international normalized ratio (INR) above the therapeutic range confers a predisposition to bleeding, 3 which is a common cause of hospital admission. 4 Polymorphisms in two genes, CYP2C9 (involved in the metabolism of the pharmacologically more potent S -enantiomer of warfarin) and VKORC1 (involved in the vitamin K cycle), 5 , 6 together with age and body-surface area, account for about 50% . . .

Circulating biomarkers are associated with the development of coronary heart disease (CHD) and its complications by reflecting pathophysiological pathways and/or organ dysfunction. We explored the associations between 157 cardiovascular (CV) and inflammatory biomarkers and CV death using proximity extension assays (PEA) in patients with chronic CHD. The derivation cohort consisted of 605 cases with CV death and 2,788 randomly selected non-cases during 3-5 years follow-up included in the STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY (STABILITY) trial between 2008 and 2010. The replication cohort consisted of 245 cases and 1,042 non-cases during 12 years follow-up included in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study between 1997 and 2000. Biomarker levels were measured with conventional immunoassays and/or with the OLINK PEA panels CVD I and Inflammation. Associations with CV death were evaluated by Random Survival Forest (RF) and Cox regression analyses. Both cohorts had the same median age (65 years) and 20% smokers, while there were slight differences in male sex (82% and 76%), hypertension (70% and 78%), and diabetes (39% and 30%) in the respective STABILITY and LURIC cohorts. The analyses identified 18 biomarkers with confirmed independent association with CV death by Boruta analyses and statistical significance (all p < 0.0001) by Cox regression when adjusted for clinical characteristics in both cohorts. Most prognostic information was carried by N-terminal prohormone of brain natriuretic peptide (NTproBNP), hazard ratio (HR for 1 standard deviation [SD] increase of the log scale of the distribution of the biomarker in the replication cohort) 2.079 (95% confidence interval [CI] 1.799-2.402), and high-sensitivity troponin T (cTnT-hs) HR 1.715 (95% CI 1.491-1.973). The other proteins with independent associations were growth differentiation factor 15 (GDF-15) HR 1.728 (95% CI 1.527-1.955), transmembrane immunoglobulin and mucin domain protein (TIM-1) HR 1.555 (95% CI 1.362-1.775), renin HR 1.501 (95% CI 1.305-1.727), osteoprotegerin (OPG) HR 1.488 (95% CI 1.297-1.708), soluble suppression of tumorigenesis 2 protein (sST2) HR 1.478 (95% CI 1.307-1.672), cystatin-C (Cys-C) HR 1.370 (95% CI 1.243-1.510), tumor necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2) HR 1.205 (95% CI 1.131-1.285), carbohydrate antigen 125 (CA-125) HR 1.347 (95% CI 1.226-1.479), brain natriuretic peptide (BNP) HR 1.399 (95% CI 1.255-1.561), interleukin 6 (IL-6) HR 1.478 (95% CI 1.316-1.659), hepatocyte growth factor (HGF) HR 1.259 (95% CI 1.134-1.396), spondin-1 HR 1.295 (95% CI 1.156-1.450), fibroblast growth factor 23 (FGF-23) HR 1.349 (95% CI 1.237-1.472), chitinase-3 like protein 1 (CHI3L1) HR 1.284 (95% CI 1.129-1.461), tumor necrosis factor receptor 1 (TNF-R1) HR 1.486 (95% CI 1.307-1.689), and adrenomedullin (AM) HR 1.750 (95% CI 1.490-2.056). The study is limited by the differences in design, size, and length of follow-up of the 2 studies and the lack of results from coronary angiograms and follow-up of nonfatal events. Profiles of levels of multiple plasma proteins might be useful for the identification of different pathophysiological pathways associated with an increased risk of CV death in patients with chronic CHD. ClinicalTrials.gov NCT00799903.

Prediction models are the key to individualized drug therapy. Warfarin is a typical example of where pharmacogenetics could help the individual patient by modeling the dose, based on clinical factors and genetic variation in and . Clinical studies aiming to show whether pharmacogenetic warfarin dose predictions are superior to conventional initiation of warfarin are now underway. This review provides a broad view over the field of warfarin pharmacogenetics from basic knowledge about the drug, how it is monitored, factors affecting dose requirement, prediction models in general and different types of prediction models for warfarin dosing.

We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5 x 10(-7)) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that approximately 30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another approximately 12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10(-78)) at SNPs clustering near VKORC1 and the second lowest p-values (p<10(-31)) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p = 8.3 x 10(-10)) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.

A genetic predisposition to central nervous system (CNS) toxicity induced by antimicrobial drugs (antibiotics, antivirals, antifungals, and antiparasitic drugs) has been suspected. Whole genome sequencing of 66 cases and 833 controls was performed to investigate whether antimicrobial drug-induced CNS toxicity was associated with genetic variation. The primary objective was to test whether antimicrobial-induced CNS toxicity was associated with seventeen efflux transporters at the blood-brain barrier. In this study, variants or structural elements in efflux transporters were not significantly associated with CNS toxicity. Secondary objectives were to test whether antimicrobial-induced CNS toxicity was associated with genes over the whole genome, with HLA, or with structural genetic variation. Uncommon variants in and close to three genes were significantly associated with CNS toxicity according to a sequence kernel association test combined with an optimal unified test (SKAT-O). These genes were LCP1 (q = 0.013), RETSAT (q = 0.013) and SFMBT2 (q = 0.035). Two variants were driving the LCP1 association: rs6561297 (p = 1.15x10 -6 , OR: 4.60 [95% CI: 2.51–8.46]) and the regulatory variant rs10492451 (p = 1.15x10 -6 , OR: 4.60 [95% CI: 2.51–8.46]). No common genetic variant, HLA-type or structural variation was associated with CNS toxicity. In conclusion, CNS toxicity due to antimicrobial drugs was associated with uncommon variants in LCP1, RETSAT and SFMBT2.

Treatment of cardiovascular diseases (CVD) is a substantial burden to healthcare systems worldwide. New tools are needed to improve precision of treatment by optimizing the balance between efficacy, safety, and cost. We developed a high-throughput multi-marker decision support instrument which simultaneously quantifies proteins associated with CVD. Candidate proteins independently associated with different clinical outcomes were selected from clinical studies by the screening of 368 circulating biomarkers. We then custom-designed a quantitative PEA-panel with 21 proteins (CVD-21) by including recombinant antigens as calibrator samples for normalization and absolute quantification of the proteins. The utility of the CVD-21 tool was evaluated in plasma samples from a case-control cohort of 4224 patients with chronic coronary syndrome (CCS) using multivariable Cox regression analyses and machine learning techniques. The assays in the CVD-21 tool gave good precision and high sensitivity with lower level of determination (LOD) between 0.03-0.7 pg/ml for five of the biomarkers. The dynamic range for the assays was sufficient to accurately quantify the biomarkers in the validation study except for troponin I, which in the modeling was replaced by high-sensitive cardiac troponin T (hs-TnT). We created seven different multimarker models, including a reference model with NT-proBNP, hs-TnT, GDF-15, IL-6, and cystatin C and one model with only clinical variables, for the comparison of the discriminative value of the CVD-21 tool. All models with biomarkers including hs-TnT provided similar discrimination for all outcomes, e.g. c-index between 0.68-0.86 and outperformed models using only clinical variables. Most important prognostic biomarkers were MMP-12, U-PAR, REN, VEGF-D, FGF-23, TFF3, ADM, and SCF. The CVD-21 tool is the very first instrument which with PEA simultaneously quantifies 21 proteins with associations to different CVD. Novel pathophysiologic and prognostic information beyond that of established biomarkers were identified by a number of proteins.

Acute coronary syndrome (ACS) is a major cause of mortality worldwide. We have previously shown that increased interleukin-10 (IL-10) levels are associated with poor outcome in ACS patients. We performed a genome-wide association study in 2864 ACS patients and 408 healthy controls, to identify genetic variants associated with IL-10 levels. Then haplotype analyses of the identified loci were done and comparisons to levels of IL-10 and other known ACS related biomarkers. Genetic variants at the ABO blood group locus associated with IL-10 levels (top SNP: rs676457, P = 4.4 × 10-10) were identified in the ACS patients. Haplotype analysis, using SNPs tagging the four main ABO antigens (A1, A2, B and O), showed that O and A2 homozygous individuals, or O/A2 heterozygotes have much higher levels of IL-10 compared to individuals with other antigen combinations. In the ACS patients, associations between ABO antigens and von Willebrand factor (VWF, P = 9.2 × 10-13), and soluble tissue factor (sTF, P = 8.6 × 10-4) were also found. In the healthy control cohort, the associations with VWF and sTF were similar to those in ACS patients (P = 1.2 × 10-15 and P = 1.0 × 10-5 respectively), but the healthy cohort showed no association with IL-10 levels (P>0.05). In the ACS patients, the O antigen was also associated with an increased risk of cardiovascular death, all causes of death, and recurrent myocardial infarction (odds ratio [OR] = 1.24-1.29, P = 0.029-0.00067). Our results suggest that the ABO antigens play important roles, not only for the immunological response in ACS patients, but also for the outcome of the disease.

Angioedema in the mouth or upper airways is a feared adverse reaction to angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) treatment, which is used for hypertension, heart failure and diabetes complications. This candidate gene and genome-wide association study aimed to identify genetic variants predisposing to angioedema induced by these drugs. The discovery cohort consisted of 173 cases and 4890 controls recruited in Sweden. In the candidate gene analysis, ETV6, BDKRB2, MME, and PRKCQ were nominally associated with angioedema (p < 0.05), but did not pass Bonferroni correction for multiple testing (p < 2.89 × 10−5). In the genome-wide analysis, intronic variants in the calcium-activated potassium channel subunit alpha-1 (KCNMA1) gene on chromosome 10 were significantly associated with angioedema (p < 5 × 10−8). Whilst the top KCNMA1 hit was not significant in the replication cohort (413 cases and 599 ACEi-exposed controls from the US and Northern Europe), a meta-analysis of the replication and discovery cohorts (in total 586 cases and 1944 ACEi-exposed controls) revealed that each variant allele increased the odds of experiencing angioedema 1.62 times (95% confidence interval 1.05–2.50, p = 0.030). Associated KCNMA1 variants are not known to be functional, but are in linkage disequilibrium with variants in transcription factor binding sites active in relevant tissues. In summary, our data suggest that common variation in KCNMA1 is associated with risk of angioedema induced by ACEi or ARB treatment. Future whole exome or genome sequencing studies will show whether rare variants in KCNMA1 or other genes contribute to the risk of ACEi- and ARB-induced angioedema.

This genome-wide association study (GWAS) explores the genetic components of severe adverse events following COVID-19 vaccination, with focus on myocarditis and pericarditis. Three SNPs (rs536572545, rs146289966 and rs142297026) near the SCAF11 gene were linked to pericarditis, while rs570375365 in the LRRC4C gene was associated with myocarditis. These findings suggest that genetic variants may influence inflammation pathways, providing a basis for further investigation into the immunological responses triggered by vaccines.

Ulcerative colitis (UC) associated with primary sclerosing cholangitis (PSC-UC) is considered a unique inflammatory bowel disease (IBD) entity. PSC diagnosis in an IBD individual entails a significantly higher risk of gastrointestinal cancer; however, biomarkers for identifying patients with UC at risk for PSC are lacking. We, therefore, performed a thorough PSC-UC biomarker study, starting from archived colonic tissue. Proteins were extracted out of formalin-fixed paraffin-embedded proximal colon samples from PSC-UC (n = 9), UC (n = 7), and healthy controls (n = 7). Patients with IBD were in clinical and histological remission, and all patients with UC had a history of pancolitis. Samples were processed by the multienzyme digestion FASP and subsequently analyzed by liquid chromatography-tandem mass spectrometry. Candidate proteins were replicated in an independent cohort (n: PSC-UC = 16 and UC = 21) and further validated by immunohistochemistry. In the discovery step, 7,279 unique proteins were detected. The top 5 most differentiating proteins (PSC-UC vs UC) based on linear regression analysis were selected for replication. Of these, 1-acetylglycerol-3-phosphate O-acyltransferase 1 (AGPAT1) was verified as higher in PSC-UC than UC (P = 0.009) in the replication cohort. A difference on the group level was also confirmed by immunohistochemistry, showing more intense AGPAT1 staining in patients with PSC-UC compared with UC. We present AGPAT1 as a potential colonic biomarker for differentiating PSC-UC from UC. Our findings have possible implication for future PSC-IBD diagnostics and surveillance.