[Association between coagulation function indicators and placental abruption among preeclampsia-eclampsia pregnant women]

Objective: To explore the association between coagulation function indicators and placental abruption (PA) in different trimesters of pregnancy among preeclampsia-eclampsia pregnant women. Methods: From February 2018 to December 2020, pregnant women who participated in the China birth cohort study and were diagnosed with preeclampsia, eclampsia and chronic hypertension with superimposed preeclampsia in Beijing Obstetrics and Gynecology Hospital were enrolled in this study. The baseline and follow-up information were collected by questionnaire survey, and the coagulation function indicators in the first and third trimesters were obtained through medical records. The Cox proportional hazards model was used to analyze the association between the coagulation function indicators and PA. A restrictive cubic spline curve was used to draw the dose-response curve between the relevant coagulation function indicators and PA. Results: A total of 1 340 participants were included in this study. The age was (32.50±4.24) and the incidence of PA was 4.4% (59/1 340). After adjusting for relevant factors, Cox proportional hazards model showed that compared with the high-level classification of fibrinogen (FIB), participants within the middle-(HR=3.28, 95%CI: 1.27-8.48) and low-level (HR=3.84, 95%CI: 1.40-10.53) classification during the first trimester and within the low-level classification (HR=4.18, 95%CI: 1.68-10.39) during the third trimester were more likely to experience PA. Compared with the middle-level classification of pro-thrombin time (PT), the risk of PA in the participants within the low-level classification (HR=2.67, 95%CI: 1.48-4.82) was significantly higher in the third trimester. The restrictive cubic spline analysis showed a linear negative association between FIB and PA in the first and third trimesters, while PT and PA showed an approximately L-shaped association. Conclusion: Among pregnant women diagnosed with preeclampsia-eclampsia, the middle-and low-level classification of FIB in the first and third trimesters and the low-level classification of PT in the third trimester could increase the risk of PA.

[Analysis of incidence and associated factors of preterm birth based on pre-pregnancy body mass index stratification]

Objective: To analyze the incidence of preterm birth based on pre-pregnancy body mass index (BMI) stratification and explore the associated factors of preterm birth among pregnant women at different BMI stratifications. Methods: From February 2018 to December 2020, pregnant women who participated in China Birth Cohort Study (CBCS) and gave birth at Beijing Obstetrics and Gynecology Hospital were enrolled as the study subjects. Electronic Data Capture System and standard structured questionnaires were used to collect data related to pre-pregnancy, pregnancy, and delivery for pregnant women. Pregnant women were divided into the low-weight group, normal-weight group and overweight group based on their pre-pregnancy BMI. A Cox proportional hazards model was used to analyze the associated factors of preterm birth among pregnant women with different BMI before pregnancy. Results: A total of 27 195 singleton pregnant women were included, with a preterm birth rate of 5.08% (1 381/27 195). The preterm birth rates in the low-weight group, normal-weight group and overweight group were 4.29% (138/3 219), 4.63% (852/18 390) and 7.00% (391/5 586) respectively (P<0.001). After adjusting for relevant factors, the Cox proportional hazards model showed that the risk of preterm birth in the overweight group was 1.457 times higher than that in the normal-weight group (95%CI: 1.292-1.643). Preeclampsia-eclampsia (HR=2.701, 95%CI: 1.318-5.537) was the associated factor for preterm birth in the low-weight group. Advanced maternal age (HR=1.232, 95%CI: 1.054-1.441), history of preterm birth (HR=4.647, 95%CI: 3.314-6.515), vaginal bleeding in early pregnancy (HR=1.613, 95%CI: 1.380-1.884), and preeclampsia-eclampsia (HR=3.553, 95%CI: 2.866-4.404) were associated factors for preterm birth in the normal-weight group. Advanced maternal age (HR=1.473, 95%CI: 1.193-1.818), history of preterm birth (HR=3.209, 95%CI: 1.960-5.253), vaginal bleeding in early pregnancy (HR=1.636, 95%CI: 1.301-2.058), preeclampsia-eclampsia (HR=2.873, 95%CI:2.265-3.643), and pre-gestational diabetes mellitus (HR=1.867, 95%CI: 1.283-2.717) were associated factors for preterm birth in the overweight group. Conclusion: Pre-pregnancy overweight is an associated factor for preterm birth, and there are significant differences in the associated factors of preterm birth among pregnant women with different BMI before pregnancy.

A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients

Diversity in pharmacogenomic studies is poor, especially in relation to the inclusion of black African patients. Lack of funding and difficulties in recruitment, together with the requirement for large sample sizes because of the extensive genetic diversity in Africa, are amongst the factors which have hampered pharmacogenomic studies in Africa. Warfarin is widely used in sub-Saharan Africa, but as in other populations, dosing is highly variable due to genetic and non-genetic factors. In order to identify genetic factors determining warfarin response variability, we have conducted a genome-wide association study (GWAS) of plasma concentrations of warfarin enantiomers/metabolites in sub-Saharan black-Africans. This overcomes the issue of non-adherence and may have greater sensitivity at genome-wide level, to identify pharmacokinetic gene variants than focusing on mean weekly dose, the usual end-point used in previous studies. Participants recruited at 12 outpatient sites in Uganda and South Africa on stable warfarin dose were genotyped using the Illumina Infinium H3Africa Consortium Array v2. Imputation was conducted using the 1,000 Genomes Project phase III reference panel. Warfarin/metabolite plasma concentrations were determined by high-performance liquid chromatography with tandem mass spectrometry. Multivariable linear regression was undertaken, with adjustment made for five non-genetic covariates and ten principal components of genetic ancestry. After quality control procedures, 548 participants and 17,268,054 SNPs were retained. CYP2C9*8, CYP2C9*9, CYP2C9*11, and the CYP2C cluster SNP rs12777823 passed the Bonferroni-adjusted replication significance threshold (p < 3.21E-04) for warfarin/metabolite ratios. In an exploratory GWAS analysis, 373 unique SNPs in 13 genes, including CYP2C9*8, passed the Bonferroni-adjusted genome-wide significance threshold (p < 3.846E-9), with 325 (87%, all located on chromosome 10) SNPs being associated with the S-warfarin/R-warfarin outcome (top SNP rs11188082, CYP2C19 intron variant, p = 1.55E-17). Approximately 69% of these SNPs were in linkage disequilibrium (r² > 0.8) with CYP2C9*8 (n = 216) and rs12777823 (n = 8). Using a pharmacokinetic approach, we have shown that variants other than CYP2C9*2 and CYP2C9*3 are more important in sub-Saharan black-Africans, mainly due to the allele frequencies. In exploratory work, we conducted the first warfarin pharmacokinetics-related GWAS in sub-Saharan Africans and identified novel SNPs that will require external replication and functional characterization before they can be considered for inclusion in warfarin dosing algorithms.

Hamiltonian Engineering with Multicolor Drives for Fast Entangling Gates and Quantum Crosstalk Cancellation

Quantum computers built with superconducting artificial atoms already stretch the limits of their classical counterparts. While the lowest energy states of these artificial atoms serve as the qubit basis, the higher levels are responsible for both a host of attractive gate schemes as well as generating undesired interactions. In particular, when coupling these atoms to generate entanglement, the higher levels cause shifts in the computational levels that lead to unwanted ZZ quantum crosstalk. Here, we present a novel technique to manipulate the energy levels and mitigate this crosstalk with simultaneous off-resonant drives on coupled qubits. This breaks a fundamental deadlock between qubit-qubit coupling and crosstalk. In a fixed-frequency transmon architecture with strong coupling and crosstalk cancellation, additional cross-resonance drives enable a 90 ns CNOT with a gate error of (0.19±0.02)%, while a second set of off-resonant drives enables a novel CZ gate. Furthermore, we show a definitive improvement in circuit performance with crosstalk cancellation over seven qubits, demonstrating the scalability of the technique. This Letter paves the way for superconducting hardware with faster gates and greatly improved multiqubit circuit fidelities.

Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm

Warfarin remains the most widely prescribed oral anticoagulant in sub‐Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine‐learning techniques in predicting stable warfarin dose in sub‐Saharan Black‐African patients and (b) externally validated a previously developed Warfarin Anticoagulation in Patients in Sub‐Saharan Africa (War‐PATH) clinical dose–initiation algorithm. The development cohort included 364 patients recruited from eight outpatient clinics and hospital departments in Uganda and South Africa (June 2018–July 2019). Validation was conducted using an external validation cohort (270 patients recruited from August 2019 to March 2020 in 12 outpatient clinics and hospital departments). Based on the mean absolute error (MAE; mean of absolute differences between the actual and predicted doses), random forest regression (12.07 mg/week; 95% confidence interval [CI], 10.39–13.76) was the best performing machine‐learning technique in the external validation cohort, whereas the worst performing technique was model trees (17.59 mg/week; 95% CI, 15.75–19.43). By comparison, the simple, commonly used regression technique (ordinary least squares) performed similarly to more complex supervised machine‐learning techniques and achieved an MAE of 13.01 mg/week (95% CI, 11.45–14.58). In summary, we have demonstrated that simpler regression techniques perform similarly to more complex supervised machine‐learning techniques. We have also externally validated our previously developed clinical dose–initiation algorithm, which is being prospectively tested for clinical utility.

Developing and Validating a Clinical Warfarin Dose-Initiation Model for Black-African Patients in South Africa and Uganda

Warfarin remains the oral anticoagulant of choice in sub-Saharan Africa. However, dosing is challenging due to a highly variable clinical response for a given dose. This study aimed to develop and validate a clinical warfarin dose-initiation model in sub-Saharan Black-African patients. For the development cohort, we used data from 364 patients who were recruited from 8 outpatient clinics and hospital departments in Uganda and South Africa (June 2018-July 2019). Validation was undertaken using the International Warfarin Pharmacogenetics Consortium (IWPC) dataset (690 black patients). Four predictors (age, weight, target International Normalized Ratio range, and HIV status) were included in the final model, which achieved mean absolute errors (MAEs; mean of absolute differences between true dose and dose predicted by the model) of 11.6 (95% confidence interval (CI) 10.4-12.8) and 12.5 (95% CI 11.6-13.4) mg/week in the development and validation cohorts, respectively. Two other clinical models, IWPC and Gage, respectively, obtained MAEs of 12.5 (95% CI 11.3-13.7) and 12.7 (95% CI 11.5-13.8) mg/week in the development cohort, and 12.1 (95% CI 11.2-13.0) and 12.2 (95% CI 11.4-13.1) mg/week in the validation cohort. Compared with fixed dose-initiation, our model decreased the percentage of patients at high risk of suboptimal anticoagulation by 7.5% (1.5-13.7%) and 11.9% (7.1-16.8%) in the development and validation cohorts, respectively. The clinical utility of this model will be tested in a prospective study. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? ☑ Warfarin dosing remains challenging due to a highly variable clinical response for a given dose. WHAT QUESTION DID THIS STUDY ADDRESS? ☑ Can a clinical dose-initiation model be developed and validated for sub-Saharan Black-African patients? WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? ☑ We have developed the first warfarin dose-initiation clinical model for Black-African patients in Uganda and South Africa. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? ☑ We will be implementing and validating this model in a prospective cohort to inform future large-scale implementation. More optimized dosing should improve the quality of warfarin anticoagulation in these two developing countries.

Warfarin dosing algorithms: A systematic review

Aims

Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.

Methods

We systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.

Results

Of 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.

Conclusion

Most warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under‐served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under‐represented populations should be prioritized.

Genetic Factors Influencing Warfarin Dose in Black-African Patients: A Systematic Review and Meta-Analysis

Warfarin is the most commonly used oral anticoagulant in sub-Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high interindividual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in black-Africans, we performed a meta-analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week, respectively. VKORC1 variants rs9923231 (-1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively, whereas rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in black-Africans to evaluate genetic factors determining warfarin response.

Genetic associations with clozapine-induced myocarditis in patients with schizophrenia

Clozapine is the most effective antipsychotic drug for schizophrenia, yet it can cause life-threatening adverse drug reactions, including myocarditis. The aim of this study was to determine whether schizophrenia patients with clozapine-induced myocarditis have a genetic predisposition compared with clozapine-tolerant controls. We measured different types of genetic variation, including genome-wide single-nucleotide polymorphisms (SNPs), coding variants that alter protein expression, and variable forms of human leucocyte antigen (HLA) genes, alongside traditional clinical risk factors in 42 cases and 67 controls. We calculated a polygenic risk score (PRS) based on variation at 96 different genetic sites, to estimate the genetic liability to clozapine-induced myocarditis. Our genome-wide association analysis identified four SNPs suggestive of increased myocarditis risk (P < 1 × 10^-6), with odds ratios ranging 5.5-13.7. The SNP with the lowest P value was rs74675399 (chr19p13.3, P = 1.21 × 10^-7; OR = 6.36), located in the GNA15 gene, previously associated with heart failure. The HLA-C*07:01 allele was identified as potentially predisposing to clozapine-induced myocarditis (OR = 2.89, 95% CI: 1.11-7.53), consistent with a previous report of association of the same allele with clozapine-induced agranulocytosis. Another seven HLA alleles, including HLA-B*07:02 (OR = 0.25, 95% CI: 0.05-1.2) were found to be putatively protective. Long-read DNA sequencing provided increased resolution of HLA typing and validated the HLA associations. The PRS explained 66% of liability (P value = 9.7 × 10^-5). Combining clinical and genetic factors together increased the proportion of variability accounted for (r² 0.73, P = 9.8 × 10^-9). However, due to the limited sample size, individual genetic associations were not statistically significant after correction for multiple testing. We report novel candidate genetic associations with clozapine-induced myocarditis, which may have potential clinical utility, but larger cohorts are required for replication.

Susceptibility to corticosteroid-induced adrenal suppression: a genome-wide association study

BACKGROUND

A serious adverse effect of corticosteroid therapy is adrenal suppression. Our aim was to identify genetic variants affecting susceptibility to corticosteroid-induced adrenal suppression.

METHODS

We enrolled children with asthma who used inhaled corticosteroids as part of their treatment from 25 sites across the UK (discovery cohort), as part of the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) study. We included two validation cohorts, one comprising children with asthma (PASS study) and the other consisting of adults with chronic obstructive pulmonary disorder (COPD) who were recruited from two UK centres for the Pharmacogenomics of Adrenal Suppression in COPD (PASIC) study. Participants underwent a low-dose short synacthen test. Adrenal suppression was defined as peak cortisol less than 350 nmol/L (in children) and less than 500 nmol/L (in adults). A case-control genome-wide association study was done with the control subset augmented by Wellcome Trust Case Control Consortium 2 (WTCCC2) participants. Single nucleotide polymorphisms (SNPs) that fulfilled criteria to be advanced to replication were tested by a random-effects inverse variance meta-analysis. This report presents the primary analysis. The PASS study is registered in the European Genome-phenome Archive (EGA). The PASS study is complete whereas the PASIC study is ongoing.

FINDINGS

Between November, 2008, and September, 2011, 499 children were enrolled to the discovery cohort. Between October, 2011, and December, 2012, 81 children were enrolled to the paediatric validation cohort, and from February, 2010, to June, 2015, 78 adults were enrolled to the adult validation cohort. Adrenal suppression was present in 35 (7%) children in the discovery cohort and six (7%) children and 17 (22%) adults in the validation cohorts. In the discovery cohort, 40 SNPs were found to be associated with adrenal suppression (genome-wide significance p<1 × 10-6), including an intronic SNP within the PDGFD gene locus (rs591118; odds ratio [OR] 7·32, 95% CI 3·15-16·99; p=5·8 × 10-8). This finding for rs591118 was validated successfully in both the paediatric asthma (OR 3·86, 95% CI 1·19-12·50; p=0·02) and adult COPD (2·41, 1·10-5·28; p=0·03) cohorts. The proportions of patients with adrenal suppression by rs591118 genotype were six (3%) of 214 patients with the GG genotype, 15 (6%) of 244 with the AG genotype, and 22 (25%) of 87 with the AA genotype. Meta-analysis of the paediatric cohorts (discovery and validation) and all three cohorts showed genome-wide significance of rs591118 (respectively, OR 5·89, 95% CI 2·97-11·68; p=4·3 × 10-9; and 4·05, 2·00-8·21; p=3·5 × 10-10).

INTERPRETATION

Our findings suggest that genetic variation in the PDGFD gene locus increases the risk of adrenal suppression in children and adults who use corticosteroids to treat asthma and COPD, respectively.

FUNDING

Department of Health Chair in Pharmacogenetics.

Genetic variation in CFH predicts phenytoin-induced maculopapular exanthema in European-descent patients

OBJECTIVE

To characterize, among European and Han Chinese populations, the genetic predictors of maculopapular exanthema (MPE), a cutaneous adverse drug reaction common to antiepileptic drugs.

METHODS

We conducted a case-control genome-wide association study of autosomal genotypes, including Class I and II human leukocyte antigen (HLA) alleles, in 323 cases and 1,321 drug-tolerant controls from epilepsy cohorts of northern European and Han Chinese descent. Results from each cohort were meta-analyzed.

RESULTS

We report an association between a rare variant in the complement factor H-related 4 (CFHR4) gene and phenytoin-induced MPE in Europeans (p = 4.5 × 10-11; odds ratio [95% confidence interval] 7 [3.2-16]). This variant is in complete linkage disequilibrium with a missense variant (N1050Y) in the complement factor H (CFH) gene. In addition, our results reinforce the association between HLA-A*31:01 and carbamazepine hypersensitivity. We did not identify significant genetic associations with MPE among Han Chinese patients.

CONCLUSIONS

The identification of genetic predictors of MPE in CFHR4 and CFH, members of the complement factor H-related protein family, suggest a new link between regulation of the complement system alternative pathway and phenytoin-induced hypersensitivity in European-ancestral patients.

A multi-factorial analysis of response to warfarin in a UK prospective cohort

Background

Warfarin is the most widely used oral anticoagulant worldwide, but it has a narrow therapeutic index which necessitates constant monitoring of anticoagulation response. Previous genome-wide studies have focused on identifying factors explaining variance in stable dose, but have not explored the initial patient response to warfarin, and a wider range of clinical and biochemical factors affecting both initial and stable dosing with warfarin.

Methods

A prospective cohort of 711 patients starting warfarin was followed up for 6 months with analyses focusing on both non-genetic and genetic factors. The outcome measures used were mean weekly warfarin dose (MWD), stable mean weekly dose (SMWD) and international normalised ratio (INR) > 4 during the first week. Samples were genotyped on the Illumina Human610-Quad chip. Statistical analyses were performed using Plink and R.

Results

VKORC1 and CYP2C9 were the major genetic determinants of warfarin MWD and SMWD, with CYP4F2 having a smaller effect. Age, height, weight, cigarette smoking and interacting medications accounted for less than 20 % of the variance. Our multifactorial analysis explained 57.89 % and 56.97 % of the variation for MWD and SMWD, respectively. Genotypes for VKORC1 and CYP2C9*3, age, height and weight, as well as other clinical factors such as alcohol consumption, loading dose and concomitant drugs were important for the initial INR response to warfarin. In a small subset of patients for whom data were available, levels of the coagulation factors VII and IX (highly correlated) also played a role.

Conclusion

Our multifactorial analysis in a prospectively recruited cohort has shown that multiple factors, genetic and clinical, are important in determining the response to warfarin. VKORC1 and CYP2C9 genetic polymorphisms are the most important determinants of warfarin dosing, and it is highly unlikely that other common variants of clinical importance influencing warfarin dosage will be found. Both VKORC1 and CYP2C9*3 are important determinants of the initial INR response to warfarin. Other novel variants, which did not reach genome-wide significance, were identified for the different outcome measures, but need replication.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0255-y) contains supplementary material, which is available to authorized users.

[Chemical constituents from the bark of Hibiscus syriacus L]

Seven constituents (I-VII) were isolated from the bark of Hibiscus syriacus and identified as nonanedioic acid (I), suberic acid (II), 1-octarcosanol (III), beta-sitosterol (IV), 1,22-docosanediol (V), betulin (VI) and erythrotriol (VII). VII was obtained from the plant for the first time, I, II, III and VI were isolated from Malvaceae plants for the first time.