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ContextExtremely early age at menarche, also called precocious puberty, has been associated with various cardiometabolic traits, but their shared heritability remains unclear.ObjectivesThis work aimed to identify new shared genetic variants and their pathways for age at menarche and cardiometabolic traits and to investigate the influence of central precocious puberty on childhood cardiometabolic traits.MethodsUsing the conjunction false discovery rate method, this study analyzed genome-wide association study data from the menarche-cardiometabolic traits among 59 655 females of Taiwanese ancestry and systemically investigated pleiotropy between age at menarche and cardiometabolic traits. To support the novel hypertension link, we used the Taiwan Puberty Longitudinal Study (TPLS) to investigate the influence of precocious puberty on childhood cardiometabolic traits.ResultsWe discovered 27 novel loci, with an overlap between age at menarche and cardiometabolic traits, including body fat and blood pressure. Among the novel genes discovered, SEC16B, CSK, CYP1A1, FTO, and USB1 are within a protein interaction network with known cardiometabolic genes, including traits for obesity and hypertension. These loci were confirmed through demonstration of significant changes in the methylation or expression levels of neighboring genes. Moreover, the TPLS provided evidence regarding a 2-fold higher risk of early-onset hypertension that occurred in girls with central precocious puberty.ConclusionOur study highlights the usefulness of cross-trait analyses for identifying shared etiology between age at menarche and cardiometabolic traits, especially early-onset hypertension. The menarche-related loci may contribute to early-onset hypertension through endocrinological pathways.

BackgroundFor women undergoing in vitro fertilization (IVF), the clinical benefit of embryo transfer at the blastocyst stage (Day 5) versus cleavage stage (Day 3) remains controversial. The purpose of this study is to compare the implantation rate, clinical pregnancy rate and odds of live birth of Day 3 and Day 5 embryo transfer, and more importantly, to address the issue that patients were chosen to receive either transfer protocol due to their underlying clinical characteristics, i.e., confounding by indication.MethodsWe conducted a retrospective cohort study of 9,090 IVF cycles collected by Lee Women’s Hospital in Taichung, Taiwan from 1998 to 2014. We utilized the method of propensity score matching to mimic a randomized controlled trial (RCT) where each patient with Day 5 transfer was matched by another patient with Day 3 transfer with respect to other clinical characteristics. Implantation rate, clinical pregnancy rate, and odds of live birth were compared for women underwent Day 5 transfer and Day 3 transfer to estimate the causal effects. We further investigated the causal effects in subgroups by stratifying age and anti-Mullerian hormone (AMH).ResultsOur analyses uncovered an evidence of a significant difference in implantation rate (p=0.04) favoring Day 5 transfer, and showed that Day 3 and Day 5 transfers made no difference in both odds of live birth (p=0.27) and clinical pregnancy rate (p=0.11). With the increase of gestational age, the trend toward non-significance of embryo transfer day in our result appeared to be consistent for subgroups stratified by age and AMH, while all analyses stratified by age and AMH were not statistically significant.ConclusionsWe conclude that for women without strong indications for Day 3 or Day 5 transfer, there is a small significant difference in implantation rate in favor of Day 5 transfer. However, the two protocols have indistinguishable outcomes on odds of live birth and clinical pregnancy rate.

Mediation analyses can help us to understand the biological mechanism in which an exposure or treatment affects an outcome. Single mediator analyses have been used in various applications, but may not be appropriate for analyzing intricate mechanisms involving multiple mediators that affect each other. Thus, in this article, we studied multiple sequentially ordered mediators for a dichotomous outcome and presented the identifiability assumptions for the path-specific effects on the outcome, that is, the effect of an exposure on the outcome mediated by a specific set of mediators. We proposed a closed-form estimator for the path-specific effects by modeling the dichotomous outcome using a probit model. Asymptotic variance of the proposed estimator is derived and can be approximated via delta method or bootstrapping. Simulations under a finite sample showed the validity of our method in capturing the path-specific effects when the probability of each potential counterfactual outcome is not small and demonstrated the utility of a computationally efficient alternative to bootstrapping for calculating variance. The method is applied to investigate the effects of polycystic ovarian syndrome on live birth rates mediated by estradiol levels and the number of oocytes retrieved in a large electronic in vitro fertilization database. We implemented the method into an R package SOMM, which is available at https://github.com/roqe/SOMM.

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

Background Direct oral anticoagulants (DOACs) have a better risk benefit profile in Asian patients with atrial fibrillation (AF). Whether treatment effects could be modified by drug class and dependency on renal elimination of studied agents has not yet been explored. Methods We searched PubMed, CENTRAL, and CINAHL databases through November 2016 for phase III randomized controlled trials comparing DOACs with warfarin in patients with AF. Efficacy and safety outcomes were pooled according to drug class and dependency on renal elimination of DOACs and were compared with the Mantel-Haenszel fixed-effects model. Effect differences were assessed with Bucher's indirect comparisons using common estimates, once heterogeneity was low, and with the Bayesian method. Results Among 6496 Asian patients from 6 trials, both direct thrombin inhibitors and factor Xa inhibitors, compared with warfarin, were associated with lower risks of stroke or systemic embolism and major bleeding (risk ratio [95% confidence interval], 0.51 [0.33-0.78], 0.74 ([0.58-0.96], 0.60 [0.41-0.86], and 0.59 [0.47-0.76], respectively). There was no between-group difference in direct thrombin inhibitors and factor Xa inhibitors or in DOACs with renal elimination less than 50% and 50% or greater (all I2 .05). Indirect comparisons within strata of drug class and dependency on renal elimination showed no preferential effect of any given regimen over another. There was no difference in effects on ischemic and hemorrhagic stroke, intracranial hemorrhage, myocardial infarction, and all-cause mortality between DOACs stratified by pharmacologic characteristics. Conclusions DOACs, as a therapeutic class, outperform warfarin in efficacy and safety in Asian patients with AF.

Background Although randomized controlled trials (RCTs) indicated that standard dose non–vitamin K antagonist oral anticoagulants (NOACs) were more compelling, low dose NOACs are commonly used in clinical practice in Asia. Objective The purpose of this study was to assess the relative therapeutic benefit and risk of standard dose vs low dose NOACs in Asian patients enrolled in contemporary RCTs. Methods We performed a prespecified meta-analysis of 3155 Asian patients with NOACs in the RE-LY (Randomized Evaluation of Long-Term Anticoagulation Therapy) and ENGAGE AF-TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48) trials. Efficacy and safety with standard dose vs low dose NOACs were compared by risk ratios (RRs) and 95% confidence intervals (CIs) in a random-effects model. An evidence network incorporating additional Asian patients from ROCKET AF, J- ROCKET AF, and ARISTOTLE was constructed with the Bayesian method. Results Risks of stroke or systemic embolism and ischemic stroke were significantly reduced with standard dose vs low dose NOACs (RR 0.62, 95% CI 0.45–0.85; and RR 0.55, 95% CI 0.38–0.79, respectively). Rates of major, intracranial, and life-threatening bleeding with 2 dosing regimens were broadly similar (RR 1.31, 95% CI 0.74–2.33; RR 1.54, 95% CI 0.72–3.30; and RR 1.49, 95% CI 0.87–2.55, respectively). Absolute rates of all-cause mortality and the net clinical outcome with standard dose NOACs were lower but not statistically significant (absolute reduction 0.4% per year and 1.1% per year, respectively). Network meta-analyses demonstrated that standard dose NOACs had the most favorable risk–benefit profile among oral anticoagulants. Conclusion In Asian patients, standard dose NOACs represent a more appealing therapeutic option than low dose NOACs, with a significant reduction in ischemic stroke without an excess of major bleeding.

Background/Purpose Non-vitamin K antagonist oral anticoagulants (NOACs) have a half-life of around 12 h. We aimed to clarify if there was any effect modification by dosing (once- or twice-daily) regimens in Asian patients. Methods Phase III randomized controlled trials of NOACs compared with warfarin in Asian patients with atrial fibrillation (AF) were identified and extracted from PubMed, CENTRAL, and CINAHL databases through November 2016. Outcomes were pooled by dosing regimens with the Mantel-Haenszel fixed-effects model. The risk ratio (RR) and 95% confidence interval (CI) were calculated. Effect differences between once- and twice-daily NOACs were assessed with Bucher indirect comparisons using common estimates, once heterogeneity was low, and with the Bayesian method. Results From 6 trials, there was no effect modification by dosing regimens in the risk of stroke or systemic embolism across ethnicities (all interaction P > 0.05). Both dosing regimens were associated with a greater reduction in the risk of major bleeding in Asian patients (RR, 0.63 (95% CI, 0.47–0.85) and 0.57 (95% CI, 0.43–0.75), for once- and twice-daily NOACs, respectively). In Asian patients, risks of hemorrhagic stroke and intracranial hemorrhage were lower with once- (RR, 0.41 (95% CI, 0.21–0.80) and 0.29 (95% CI, 0.16–0.53)) and twice-daily NOACs (RR, 0.25 (95% CI, 0.12–0.51) and 0.38 (95% CI, 0.23–0.65)), compared with warfarin. There was no effect difference favoring any of NOAC regimens evaluated by Bucher and Bayesian methods. Conclusion In Asian patients with AF, NOACs, regardless of dosing regimens, have a similar feature of preserved efficacy with improved safety compared with warfarin.

Background Thromboembolism prevention is central to atrial fibrillation (AF) management. Randomized controlled trials (RCTs) have primarily focused on stroke prevention. Detailed analyses of extracranial thromboembolic events, particularly in patients with low dose non–vitamin K antagonist oral anticoagulants (NOACs), are scarce. Objective The purpose of this study was to assess efficacy of NOACs in prevention of extracranial arterial and venous thromboembolism. Methods We searched PubMed, CENTRAL, and CINAHL through April 2016 for phase III RCTs of NOACs in patients with AF. Information regarding systemic embolism (SE), pulmonary embolism (PE), and deep vein thrombosis (DVT) was retrieved and compared by risk ratio (RR) and 95% confidence interval (CI) with a fixed-effects model. A network with additional RCTs involving antiplatelet agents was constructed. The surface under the cumulative ranking curve (SUCRA) of each treatment was calculated for assessing the best treatment in the network meta-analysis. Results Among 72,963 patients with AF from 5 RCTs, relative to warfarin, standard dose NOACs were associated with a lower risk of SE (RR 0.71, 95% CI 0.52–0.99) and similar risks of PE and DVT (RR 0.95, 95% CI 0.72–1.35; and RR 0.83, 95% CI 0.56–1.24, respectively). Compared with warfarin, risks of SE, PE, and DVT with low dose NOACs were similar. In network meta-analyses, standard dose NOACs were associated with the largest SUCRA for prevention of SE and PE. Conclusion In patients with AF, standard dose NOACs were the most efficacious treatment in preventing SE, whereas both dose regimens of NOACs were reasonable alternatives to warfarin in preventing venous thromboembolism.

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA., Author summary Pathway analysis is a common approach to quickly access the pathways being regulated in the experiments. There are numerous statistics to perform pathway analysis; most of them assume that the genes or proteins are independent of each other for statistical ease. This assumption, however, is unrealistic to the real biological system and may cause false positives in practice. A standard way to address this issue is to measure the associations among genes or proteins. Unfortunately, the estimation of associations requires sufficient sample size, which is usually not available for proteomic data produced by mass spectrometry. In this study, we propose a T2-statistic, which estimates the associations among gene products, to perform pathway analysis for quantitative proteomic data. Instead of calculating the associations directly from data, we use the confidence scores retrieved from protein-protein interaction databases. We also design an integrating procedure to reserve pathways of sufficient evidence as a regulated pathway group. We compare the proposed T2-statistic to other popular statistics using five published experimental datasets, and the T2-statistic yields more accurate descriptions in agreement with the discussion of the original papers.

Background When studying genetic diseases in which genetic variations are passed on to offspring, the ability to distinguish between paternal and maternal alleles is essential. Determining haplotypes from genotype data is called haplotype inference. Most existing computational algorithms for haplotype inference have been designed to use genotype data collected from individuals in the form of a pedigree. A haplotype is regarded as a hereditary unit and therefore input pedigrees are preferred that are free of mutational events and have a minimum number of genetic recombinational events. These ideas motivated the zero-recombinant haplotype configuration (ZRHC) problem, which strictly follows the Mendelian law of inheritance, namely that one haplotype of each child is inherited from the father and the other haplotype is inherited from the mother, both without any mutation. So far no linear-time algorithm for ZRHC has been proposed for general pedigrees, even though the number of mating loops in a human pedigree is usually very small and can be regarded as constant. Results Given a pedigree with n individuals, m marker loci, and k mating loops, we proposed an algorithm that can provide a general solution to the zero-recombinant haplotype configuration problem in O(kmn + k 2 m) time. In addition, this algorithm can be modified to detect inconsistencies within the genotype data without loss of efficiency. The proposed algorithm was subject to 12000 experiments to verify its performance using different (n, m) combinations. The value of k was uniformly distributed between zero and six throughout all experiments. The experimental results show a great linearity in terms of execution time in relation to input size when both n and m are larger than 100. For those experiments where n or m are less than 100, the proposed algorithm runs very fast, in thousandth to hundredth of a second, on a personal desktop computer. Conclusions We have developed the first deterministic linear-time algorithm for the zero-recombinant haplotype configuration problem. Our experimental results demonstrated the linearity of its execution time in relation to the input size. The proposed algorithm can be modified to detect inconsistency within the genotype data without loss of efficiency and is expected to be able to handle recombinant and missing data with further extension.