Natural antisense transcript of Period2, Per2AS, regulates the amplitude of the mouse circadian clock.

In mammals, a set of core clock genes form transcription-translation feedback loops to generate circadian oscillations. We and others recently identified a novel transcript at the Period2 (Per2) locus that is transcribed from the antisense strand of Per2 This transcript, Per2AS, is expressed rhythmically and antiphasic to Per2 mRNA, leading to our hypothesis that Per2AS and Per2 mutually inhibit each other's expression and form a double negative feedback loop. By perturbing the expression of Per2AS, we found that Per2AS transcription, but not transcript, represses Per2 However, Per2 does not repress Per2AS, as Per2 knockdown led to a decrease in the Per2AS level, indicating that Per2AS forms a single negative feedback loop with Per2 and maintains the level of Per2 within the oscillatory range. Per2AS also regulates the amplitude of the circadian clock, and this function cannot be solely explained through its interaction with Per2, as Per2 knockdown does not recapitulate the phenotypes of Per2AS perturbation. Overall, our data indicate that Per2AS is an important regulatory molecule in the mammalian circadian clock machinery. Our work also supports the idea that antisense transcripts of core clock genes constitute a common feature of circadian clocks, as they are found in other organisms.

Screening p-hackers: Dissemination noise as bait.

We show that adding noise before publishing data effectively screens [Formula: see text]-hacked findings: spurious explanations produced by fitting many statistical models (data mining). Noise creates "baits" that affect two types of researchers differently. Uninformed [Formula: see text]-hackers, who are fully ignorant of the true mechanism and engage in data mining, often fall for baits. Informed researchers, who start with an ex ante hypothesis, are minimally affected. We show that as the number of observations grows large, dissemination noise asymptotically achieves optimal screening. In a tractable special case where the informed researchers' theory can identify the true causal mechanism with very few data, we characterize the optimal level of dissemination noise and highlight the relevant trade-offs. Dissemination noise is a tool that statistical agencies currently use to protect privacy. We argue this existing practice can be repurposed to screen [Formula: see text]-hackers and thus improve research credibility.

Functional analysis of the zinc finger modules of the Saccharomyces cerevisiae splicing factor Luc7.

Identification of splice sites is a critical step in pre-messenger RNA (pre-mRNA) splicing because the definition of the exon/intron boundaries controls what nucleotides are incorporated into mature mRNAs. The intron boundary with the upstream exon is initially identified through interactions with the U1 small nuclear ribonucleoprotein (snRNP). This involves both base-pairing between the U1 snRNA and the pre-mRNA as well as snRNP proteins interacting with the 5' splice site (5'ss)/snRNA duplex. In yeast, this duplex is buttressed by two conserved protein factors, Yhc1 and Luc7. Luc7 has three human paralogs (LUC7L, LUC7L2, and LUC7L3), which play roles in alternative splicing. What domains of these paralogs promote splicing at particular sites is not yet clear. Here, we humanized the zinc finger (ZnF) domains of the yeast Luc7 protein in order to understand their roles in splice site selection using reporter assays, transcriptome analysis, and genetic interactions. Although we were unable to determine a function for the first ZnF domain, humanization of the second ZnF domain to mirror that found in LUC7L or LUC7L2 resulted in altered usage of nonconsensus 5'ss. In contrast, the corresponding ZnF domain of LUC7L3 could not support yeast viability. Further, humanization of Luc7 can suppress mutation of the ATPase Prp28, which is involved in U1 release and exchange for U6 at the 5'ss. Our work reveals a role for the second ZnF of Luc7 in splice site selection and suggests that different ZnF domains may have different ATPase requirements for release by Prp28.

Formin tails act as a switch, inhibiting or enhancing processive actin elongation.

Formins are large, multidomain proteins that nucleate new actin filaments and accelerate elongation through a processive interaction with the barbed ends of filaments. Their actin assembly activity is generally attributed to their eponymous formin homology (FH) 1 and 2 domains; however, evidence is mounting that regions outside of the FH1FH2 stretch also tune actin assembly. Here, we explore the underlying contributions of the tail domain, which spans the sequence between the FH2 domain and the C terminus of formins. Tails vary in length from ∼0 to >200 residues and contain a number of recognizable motifs. The most common and well-studied motif is the ∼15-residue-long diaphanous autoregulatory domain. This domain mediates all or nothing regulation of actin assembly through an intramolecular interaction with the diaphanous inhibitory domain in the N-terminal half of the protein. Multiple reports demonstrate that the tail can enhance both nucleation and processivity. In this study, we provide a high-resolution view of the alternative splicing encompassing the tail in the formin homology domain (Fhod) family of formins during development. While four distinct tails are predicted, we found significant levels of only two of these. We characterized the biochemical effects of the different tails. Surprisingly, the two highly expressed Fhod-tails inhibit processive elongation and diminish nucleation, while a third supports activity. These findings demonstrate a new mechanism of modulating actin assembly by formins and support a model in which splice variants are specialized to build distinct actin structures during development.

Nanoblot: an R-package for visualization of RNA isoforms from long-read RNA-sequencing data.

RT-PCR and northern blots have long been used to study RNA isoforms usage for single genes. Recent advancements in long-read sequencing have yielded unprecedented information about the usage and abundance of these RNA isoforms. However, visualization of long-read sequencing data remains challenging due to the high information density. To alleviate these issues, we have developed NanoBlot, an open-source R-package that generates northern blot and RT-PCR-like images from long-read sequencing data. NanoBlot requires aligned, positionally sorted and indexed BAM files. Plotting is based around ggplot2 and is easily customizable. Advantages of NanoBlot include a robust system for designing probes to visualize isoforms including excluding reads based on the presence or absence of a specified region, an elegant solution to representing isoforms with continuous variations in length, and the ability to overlay multiple genes in the same plot using different colors. We present examples of nanoblots compared to actual northern blot data. In addition to traditional gel-like images, the NanoBlot package can also output other visualizations such as violin plots and 3'-RACE-like plots focused on 3'-end isoforms visualization. The use of the NanoBlot package should provide a simple answer to some of the challenges of visualizing long-read RNA-sequencing data.

Sex Differences in Trends in Stroke Recurrence and Postrecurrence Mortality 2000-2020: Population-Based Brain Attack Surveillance in Corpus Christi Project.

OBJECTIVE: This study was undertaken to delineate 21-year sex-specific trends in recurrence and postrecurrence mortality. METHODS: Between 2000 and 2020, first-ever ischemic stroke (IS) patients, ascertained from the population-based BASIC (Brain Attack Surveillance in Corpus Christi) project in South Texas, were followed for recurrent stroke and all-cause mortality until December 31, 2020. Multivariable regression models with an interaction between calendar year and sex were used to estimate sex-specific trends and sex differences in recurrence and postrecurrence mortality. RESULTS: Of the 6,057 IS patients (median age = 69 years, 49.8% women), 654 (10.8%) had a recurrence and 399 (47.7%) had postrecurrence mortality during 5 years of follow-up. In 2000, women had 2.5% higher albeit non-statistically significant 5-year risk of recurrence than men in absolute scale. With the trend declining in women by 7.6% (95% confidence interval [CI] = -10.8 to -4.5%) and in men by 3.6% (95% CI = -6.5% to -0.7%), the risk at the end of the study period was 1.5% (95% CI = -0.3% to 3.6%) lower among women than men. For postrecurrence mortality, the risk was 10.2% lower among women in 2000, but the sex difference was 3.3% by the end of the period, which was due to a larger overall increase in the risk among women than men over the entire time period. INTERPRETATION: The declines in recurrent stroke suggest successful secondary stroke prevention, especially in women. However, the continued high postrecurrence mortality among both sexes at the end of study period emphasizes the need for ongoing interventions to improve prognosis in those who have had recurrent cerebrovascular events. ANN NEUROL 2024;96:332-342.

Splicing inactivation generates hybrid mRNA-snoRNA transcripts targeted by cytoplasmic RNA decay.

Many small nucleolar RNAs (snoRNA)s are processed from introns of host genes, but the importance of splicing for proper biogenesis and the fate of the snoRNAs is not well understood. Here, we show that inactivation of splicing factors or mutation of splicing signals leads to the accumulation of partially processed hybrid messenger RNA-snoRNA (hmsnoRNA) transcripts. hmsnoRNAs are processed to the mature 3' ends of the snoRNAs by the nuclear exosome and bound by small nucleolar ribonucleoproteins. hmsnoRNAs are unaffected by translation-coupled RNA quality-control pathways, but they are degraded by the major cytoplasmic exonuclease Xrn1p, due to their messenger RNA (mRNA)-like 5' extensions. These results show that completion of splicing is required to promote complete and accurate processing of intron-encoded snoRNAs and that splicing defects lead to degradation of hybrid mRNA-snoRNA species by cytoplasmic decay, underscoring the importance of splicing for the biogenesis of intron-encoded snoRNAs.

Time-varying associations of patient and tumor characteristics with cancer survival: an analysis of SEER data across 14 cancer sites, 2004-2017.

PURPOSE: Surveillance, Epidemiology, and End Results (SEER) cancer registries provides information about survival duration and cause of death for cancer patients. Baseline demographic and tumor characteristics such as age, sex, race, year of diagnosis, and tumor stage can inform the expected survival time of patients, but their associations with survival may not be constant over the post-diagnosis period. METHODS: Using SEER data, we examined if there were time-varying associations of patient and tumor characteristics on survival, and we assessed how these relationships differed across 14 cancer sites. Standard Cox proportional hazards models were extended to allow for time-varying associations and incorporated into a competing-risks framework, separately modeling cancer-specific and other-cause deaths. For each cancer site and for each of the five factors, we estimated the relative hazard ratio and absolute hazard over time in the presence of competing risks. RESULTS: Our comprehensive consideration of patient and tumor characteristics when estimating time-varying hazards showed that the associations of age, tumor stage at diagnosis, and race/ethnicity with risk of death (cancer-specific and other-cause) change over time for many cancers; characteristics of sex and year of diagnosis exhibit some time-varying patterns as well. Stage at diagnosis had the largest associations with survival. CONCLUSION: These findings suggest that proportional hazards assumptions are often violated when examining patient characteristics on cancer survival post-diagnosis. We discuss several interesting results where the relative hazards are time-varying and suggest possible interpretations. Based on the time-varying associations of several important covariates on survival after cancer diagnosis using a pan-cancer approach, the likelihood of the proportional hazards assumption being met or corresponding interpretation should be considered in survival analyses, as flawed inference may have implications for cancer care and policy.

Shared Genetic Risk Factors for Multiple Sclerosis/Psoriasis Suggest Involvement of Interleukin-17 and Janus Kinase-Signal Transducers and Activators of Transcription Signaling.

OBJECTIVE: Psoriasis and multiple sclerosis (MS) are complex immune diseases that are mediated by T cells and share multiple comorbidities. Previous studies have suggested psoriatic patients are at higher risk of MS; however, causal relationships between the two conditions remain unclear. Through epidemiology and genetics, we provide a comprehensive understanding of the relationship, and share molecular factors between psoriasis and MS. METHODS: We used logistic regression, trans-disease meta-analysis and Mendelian randomization. Medical claims data were included from 30 million patients, including 141,544 with MS and 742,919 with psoriasis. We used genome-wide association study summary statistics from 11,024 psoriatic, 14,802 MS cases, and 43,039 controls for trans-disease meta-analysis, with additional summary statistics from 5 million individuals for Mendelian randomization. RESULTS: Psoriatic patients have a significantly higher risk of MS (4,637 patients with both diseases; odds ratio [OR] 1.07, p = 1.2 × 10-5 ) after controlling for potential confounders. Using inverse variance and equally weighted trans-disease meta-analysis, we revealed >20 shared and opposing (direction of effect) genetic loci outside the major histocompatibility complex that showed significant genetic colocalization (in COLOC and COLOC-SuSiE v5.1.0). Co-expression analysis of genes from these loci further identified distinct clusters that were enriched among pathways for interleukin-17/tumor necrosis factor-α (OR >39, p < 1.6 × 10-3 ) and Janus kinase-signal transducers and activators of transcription (OR 35, p = 1.1 × 10-5 ), including genes, such as TNFAIP3, TYK2, and TNFRSF1A. Mendelian randomization found psoriasis as an exposure has a significant causal effect on MS (OR 1.04, p = 5.8 × 10-3 ), independent of type 1 diabetes (OR 1.05, p = 4.3 × 10-7 ), type 2 diabetes (OR 1.08, p = 2.3 × 10-3 ), inflammatory bowel disease (OR 1.11, p = 1.6 × 10-11 ), and vitamin D level (OR 0.75, p = 9.4 × 10-3 ). INTERPRETATION: By investigating the shared genetics of psoriasis and MS, along with their modifiable risk factors, our findings will advance innovations in treatment for patients suffering from comorbidities. ANN NEUROL 2023;94:384-397.

Stimulated Emission of Signal Photons from Dark Matter Waves.

The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors. Current dark matter searches operating in the microwave frequency range use nearly quantum-limited amplifiers. Future high frequency searches will use photon counting techniques to evade the standard quantum limit. We present a signal enhancement technique that utilizes a superconducting qubit to prepare a superconducting microwave cavity in a nonclassical Fock state and stimulate the emission of a photon from a dark matter wave. By initializing the cavity in an |n=4⟩ Fock state, we demonstrate a quantum enhancement technique that increases the signal photon rate and hence also the dark matter scan rate each by a factor of 2.78. Using this technique, we conduct a dark photon search in a band around 5.965 GHz (24.67 µeV), where the kinetic mixing angle ε≥4.35×10^{-13} is excluded at the 90% confidence level.

Individualized empirical null estimation for exact tests of healthcare quality.

United States federal agencies evaluate healthcare providers to identify, flag, and potentially penalize those that deliver low-quality care compared to national expectations. In practice, evaluation metrics are inevitably impacted by unobserved confounding factors, which reduce flagging accuracy and cause the statistics to be overdispersed relative to the theoretical null distributions. In response to this issue, several authors have proposed individualized empirical null (IEN) methods to estimate an appropriate null distribution for each provider's evaluation statistic while taking into account the provider's effective size. However, existing IEN methods require that the statistics asymptotically follow normal distributions, which often does not hold in applications with small providers or misspecified models. In this article, we develop an IEN framework for exact hypothesis tests that accounts for the impact of unobserved confounding without making any asymptotic assumptions. Simulations show that the proposed IEN method has greater flagging accuracy compared to conventional approaches. We apply these methods to evaluate dialysis facilities and transplant centers that are monitored by the Centers for Medicare and Medicaid Services.

Epidemiology and outcomes associated with enterococcal blood stream infection among liver and kidney transplant recipients.

Bloodstream infections (BSIs) account for 18% of bacterial infections in the first year after solid organ transplantation (SOT). Enterococcus accounts for up to 20% of BSIs in this population, with vancomycin-resistant enterococcus (VRE) posing a particular risk. This is a retrospective, case-control study of adult liver and kidney transplant recipients between 01/01/2016 and 06/30/2021 that characterizes the epidemiology and outcomes of enterococcal BSIs in liver and kidney transplantations at a single institution. Subjects with an enterococcal BSI within the first 6 months post-transplant were compared to those with non-enterococcal BSIs in the same period. We identified 26 subjects with enterococcal BSIs and 28 controls with non-enterococcal BSIs (n = 54; 10.3%). Cases were mostly liver transplant recipients (n = 20; 77%) with a median MELD at transplant of 33 (range 14-43); controls included 14 KT recipients (50%). Groups differed significantly (all p < .05) by factors including perioperative transfusion requirements, need for reoperation, and number of interventions post-transplant. Cases had a median time of 25.5 days to infection and controls 100.5 days (p < .0001). There were no differences in 1-year mortality between the groups. Enterococcus faecium was the predominant species of Enterococcus (n = 23; 88.5%), with a majority (91.3%) of the isolates being VRE. In our liver and kidney transplants, enterococcal BSIs occurred early among liver transplant recipients. The high incidence of VRE among E. faecium isolates in this population warrants further investigation into the optimal approach to empiric antimicrobials for bacteremia in the early post-transplant period.

Health Care Provider Clustering Using Fusion Penalty in Quasi-Likelihood.

There has been growing research interest in developing methodology to evaluate the health care providers' performance with respect to a patient outcome. Random and fixed effects models are traditionally used for such a purpose. We propose a new method, using a fusion penalty to cluster health care providers based on quasi-likelihood. Without any priori knowledge of grouping information, our method provides a desirable data-driven approach for automatically clustering health care providers into different groups based on their performance. Further, the quasi-likelihood is more flexible and robust than the regular likelihood in that no distributional assumption is needed. An efficient alternating direction method of multipliers algorithm is developed to implement the proposed method. We show that the proposed method enjoys the oracle properties; namely, it performs as well as if the true group structure were known in advance. The consistency and asymptotic normality of the estimators are established. Simulation studies and analysis of the national kidney transplant registry data demonstrate the utility and validity of our method.

MTMR3 risk alleles enhance Toll Like Receptor 9-induced IgA immunity in IgA nephropathy.

Multiple genome-wide association studies (GWASs) have reproducibly identified the MTMR3/HORMAD2/LIF/OSM locus to be associated with IgA nephropathy (IgAN). However, the causal variant(s), implicated gene(s), and altered mechanisms remain poorly understood. Here, we performed fine-mapping analyses based on GWAS datasets encompassing 2762 IgAN cases and 5803 control individuals, and identified rs4823074 as the candidate causal variant that intersects the MTMR3 promoter in B-lymphoblastoid cells. Mendelian randomization studies suggested the risk allele may modulate disease susceptibility by affecting serum IgA levels through increased MTMR3 expression. Consistently, elevated MTMR3 expression in peripheral blood mononuclear cells was observed in patients with IgAN. Further mechanistic studies in vitro demonstrated that MTMR3 increased IgA production dependent upon its phosphatidylinositol 3-phosphate binding domain. Moreover, our study provided the in vivo functional evidence that Mtmr3-/- mice exhibited defective Toll Like Receptor 9-induced IgA production, glomerular IgA deposition, as well as mesangial cell proliferation. RNA-seq and pathway analyses showed that MTMR3 deficiency resulted in an impaired intestinal immune network for IgA production. Thus, our results support the role of MTMR3 in IgAN pathogenesis by enhancing Toll Like Receptor 9-induced IgA immunity.

Accounting for total variation and robustness in profiling health care providers.

Monitoring outcomes of health care providers, such as patient deaths, hospitalizations, and hospital readmissions, helps in assessing the quality of health care. We consider a large database on patients being treated at dialysis facilities in the United States, and the problem of identifying facilities with outcomes that are better than or worse than expected. Analyses of such data have been commonly based on random or fixed facility effects, which have shortcomings that can lead to unfair assessments. A primary issue is that they do not appropriately account for variation between providers that is outside the providers' control due, for example, to unobserved patient characteristics that vary between providers. In this article, we propose a smoothed empirical null approach that accounts for the total variation and adapts to different provider sizes. The linear model provides an illustration that extends easily to other non-linear models for survival or binary outcomes, for example. The empirical null method is generalized to allow for some variation being due to quality of care. These methods are examined with numerical simulations and applied to the monitoring of survival in the dialysis facility data.

Retrospective pharmacogenetic study of psoriasis highlights the role of KLK7 in tumour necrosis factor signalling.

BACKGROUND: Multiple treatment options are available for the management of psoriasis, but clinical response varies among individual patients and no biomarkers are available to facilitate treatment selection for improved patient outcomes. OBJECTIVES: To utilize retrospective data to conduct a pharmacogenetic study to explore the potential genetic pathways associated with drug response in the treatment of psoriasis. METHODS: We conducted a retrospective pharmacogenetic study using self-evaluated treatment response from 1942 genotyped patients with psoriasis. We examined 6 502 658 genetic markers to model their associations with response to six treatment options using linear regression, adjusting for cohort variables and demographic features. We further utilized an integrative approach incorporating epigenomics, transcriptomics and a longitudinal clinical cohort to provide biological implications for the topmost signals associated with drug response. RESULTS: Two novel markers were revealed to be associated with treatment response: rs1991820 (P = 1.30 × 10-6) for anti-tumour necrosis factor (TNF) biologics; and rs62264137 (P = 2.94 × 10-6) for methotrexate, which was also associated with cutaneous mRNA expression levels of two known psoriasis-related genes KLK7 (P = 1.0 × 10-12) and CD200 (P = 5.4 × 10-6). We demonstrated that KLK7 expression was increased in the psoriatic epidermis, as shown by immunohistochemistry, as well as single-cell RNA sequencing, and its responsiveness to anti-TNF treatment was highlighted. By inhibiting the expression of KLK7, we further illustrated that keratinocytes have decreased proinflammatory responses to TNF. CONCLUSIONS: Our study implicates the genetic regulation of cytokine responses in predicting clinical drug response and supports the association between pharmacogenetic loci and anti-TNF response, as shown here for KLK7.

A cross-validation statistical framework for asymmetric data integration.

The proliferation of biobanks and large public clinical data sets enables their integration with a smaller amount of locally gathered data for the purposes of parameter estimation and model prediction. However, public data sets may be subject to context-dependent confounders and the protocols behind their generation are often opaque; naively integrating all external data sets equally can bias estimates and lead to spurious conclusions. Weighted data integration is a potential solution, but current methods still require subjective specifications of weights and can become computationally intractable. Under the assumption that local data are generated from the set of unknown true parameters, we propose a novel weighted integration method based upon using the external data to minimize the local data leave-one-out cross validation (LOOCV) error. We demonstrate how the optimization of LOOCV errors for linear and Cox proportional hazards models can be rewritten as functions of external data set integration weights. Significant reductions in estimation error and prediction error are shown using simulation studies mimicking the heterogeneity of clinical data as well as a real-world example using kidney transplant patients from the Scientific Registry of Transplant Recipients.

Concordance indices with left-truncated and right-censored data.

In the context of time-to-event analysis, a primary objective is to model the risk of experiencing a particular event in relation to a set of observed predictors. The Concordance Index (C-Index) is a statistic frequently used in practice to assess how well such models discriminate between various risk levels in a population. However, the properties of conventional C-Index estimators when applied to left-truncated time-to-event data have not been well studied, despite the fact that left-truncation is commonly encountered in observational studies. We show that the limiting values of the conventional C-Index estimators depend on the underlying distribution of truncation times, which is similar to the situation with right-censoring as discussed in Uno et al. (2011) [On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Statistics in Medicine 30(10), 1105-1117]. We develop a new C-Index estimator based on inverse probability weighting (IPW) that corrects for this limitation, and we generalize this estimator to settings with left-truncated and right-censored data. The proposed IPW estimators are highly robust to the underlying truncation distribution and often outperform the conventional methods in terms of bias, mean squared error, and coverage probability. We apply these estimators to evaluate a predictive survival model for mortality among patients with end-stage renal disease.

Pitfalls of the concordance index for survival outcomes.

Prognostic models are useful tools for assessing a patient's risk of experiencing adverse health events. In practice, these models must be validated before implementation to ensure that they are clinically useful. The concordance index (C-Index) is a popular statistic that is used for model validation, and it is often applied to models with binary or survival outcome variables. In this paper, we summarize existing criticism of the C-Index and show that many limitations are accentuated when applied to survival outcomes, and to continuous outcomes more generally. We present several examples that show the challenges in achieving high concordance with survival outcomes, and we argue that the C-Index is often not clinically meaningful in this setting. We derive a relationship between the concordance probability and the coefficient of determination under an ordinary least squares model with normally distributed predictors, which highlights the limitations of the C-Index for continuous outcomes. Finally, we recommend existing alternatives that more closely align with common uses of survival models.

Healthcare center clustering for Cox's proportional hazards model by fusion penalty.

There has been growing research interest in developing methodology to evaluate healthcare centers' performance with respect to patient outcomes. Conventional assessments can be conducted using fixed or random effects models, as seen in provider profiling. We propose a new method, using fusion penalty to cluster healthcare centers with respect to a survival outcome. Without any prior knowledge of the grouping information, the new method provides a desirable data-driven approach for automatically clustering healthcare centers into distinct groups based on their performance. An efficient alternating direction method of multipliers algorithm is developed to implement the proposed method. The validity of our approach is demonstrated through simulation studies, and its practical application is illustrated by analyzing data from the national kidney transplant registry.