Unknown Breakpoint Research Articles

The cryptic complex rearrangements involving the DMD gene: etiologic clues about phenotypical differences revealed by optical genome mapping

BackgroundDeletion or duplication in the DMD gene is one of the most common causes of Duchenne and Becker muscular dystrophy (DMD/BMD). However, the pathogenicity of complex rearrangements involving DMD, especially segmental duplications with unknown breakpoints, is not well understood. This study aimed to evaluate the structure, pattern, and potential impact of rearrangements involving DMD duplication.MethodsTwo families with DMD segmental duplications exhibiting phenotypical differences were recruited. Optical genome mapping (OGM) was used to explore the cryptic pattern of the rearrangements. Breakpoints were validated using long-range polymerase chain reaction combined with next-generation sequencing and Sanger sequencing.ResultsA multi-copy duplication involving exons 64–79 of DMD was identified in Family A without obvious clinical symptoms. Family B exhibited typical DMD neuromuscular manifestations and presented a duplication involving exons 10–13 of DMD. The rearrangement in Family A involved complex in-cis tandem repeats shown by OGM but retained a complete copy (reading frame) of DMD inferred from breakpoint validation. A reversed insertion with a segmental repeat was identified in Family B by OGM, which was predicted to disrupt the normal structure and reading frame of DMD after confirming the breakpoints.ConclusionsValidating breakpoint and rearrangement pattern is crucial for the functional annotation and pathogenic classification of genomic structural variations. OGM provides valuable insights into etiological analysis of DMD/BMD and enhances our understanding for cryptic effects of complex rearrangements.

LIMBARE: An Advanced Linear Mixed-Effects Breakpoint Analysis With Robust Estimation Method With Applications to Longitudinal Ophthalmic Studies.

Broken stick analysis is a widely used approach for detecting unknown breakpoints where the association between measurements is nonlinear. We propose LIMBARE, an advanced linear mixed-effects breakpoint analysis with robust estimation, especially designed for longitudinal ophthalmic studies. LIMBARE accommodates repeated measurements from both eyes and over time, and it effectively addresses the presence of outliers. The model setup of LIMBARE and the computing algorithm for point and confidence interval estimates of the breakpoint were introduced. The performance of LIMBARE and other competing methods was assessed via comprehensive simulation studies and application to a longitudinal ophthalmic study with 216 eyes (145 subjects) followed for an average of 3.7 ± 1.3years to examine the longitudinal association between structural and functional measurements. In simulation studies, LIMBARE showed the smallest bias and mean squared error for estimating the breakpoint, with an empirical coverage probability of corresponding confidence interval estimates closest to the nominal level for scenarios with and without outlier data points. In the application to the longitudinal ophthalmic study, LIMBARE detected two breakpoints between visual field mean deviation (MD) and retinal nerve fiber layer thickness and one breakpoint between MD and cup-to-disc ratio, whereas the cross-sectional analysis approach detected only one and none, respectively. LIMBARE enhances breakpoint estimation accuracy in longitudinal ophthalmic studies, and the cross-sectional analysis approach is not recommended for future studies. Our proposed method and companion R package provide a valuable computational tool for advancing longitudinal ophthalmology research and exploring the association relationships among ophthalmic variables.

Impacts on functional and oncological outcomes of Robotic-assisted Radical Prostatectomy 10 years after the US Preventive Service Taskforce recommendations against PSA screening.

In the following years after the United States Preventive Service Task Force (USPSTF) recommendation against prostate cancer screening with PSA in 2012, several authors worldwide described an increase in higher grades and aggressive prostate tumors. In this scenario, we aim to evaluate the potential impacts of USPSTF recommendations on the functional and oncological outcomes in patients undergoing robotic-assisted radical prostatectomy (RARP) in a referral center. We included 11396 patients who underwent RARP between 2008 and 2021. Each patient had at least a 12-month follow-up. The cohort was divided into two groups based on an inflection point in the outcomes at the end of 2012 and the beginning of 2013. The inflection point period was detected by Bayesian regression with multiple change points and regression with unknown breakpoints. We reported continuous variables as median and interquartile range (IQR) and categorical variables as absolute and relative percent frequencies. Group 1 had 4760 patients, and Group 2 had 6636 patients, with a median follow-up of 109 and 38 months, respectively. In the final pathology, Group 2 had 9.5% increase in tumor volume, 24% increase on Gleason ≥ 4+3 (ISUP 3) , and 18% increase on ≥ pT3. This translated to a 6% increase in positive surgical margins and 24% reduction in full nerve sparing in response to the worsening pathology. There was a significant decline in post-operative outcomes in Group 2, including a 12-month continence reduction of 9%, reduction in potency by 27%, and reduction of trifecta by 22%. The increasing number of high-risk patients has led to worse functional and oncologic outcomes. The initial rapid rise in PSM was leveled by the move towards more partial nerve sparing. Among somehistorical changes in prostate cancer diagnosis and management in the period of our study, theUSPSTF recommendationcoincided with worseoutcomes of prostate cancer treatment in a population who could benefit from PSA screening at the appropriate time.

Novel insights into molecular patterns of ROS1 fusions in a large Chinese NSCLC cohort: a multicenter study.

ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) rearrangements are a crucial therapeutic target in non-small cell lung cancer (NSCLC). However, there is limited comprehensive analysis of the molecular patterns of ROS1 fusions. This study aimed to address this gap by analysing 135 ROS1 fusions from 134 Chinese NSCLC patients using next-generation sequencing (NGS). The fusions were categorized into common and uncommon based on their incidence. Our study revealed, for the first time, a unique distribution preference of breakpoints within ROS1, with common fusions occurring in introns 31-33 and uncommon fusions occurring in introns 34 and 35. Additionally, we identified previously unknown breakpoints within intron 28 of ROS1. Furthermore, we identified a close association between the distribution patterns of fusion partners and breakpoints on ROS1, providing important insights into the molecular landscape of ROS1 fusions. We also confirmed the presence of inconsistent breakpoints in ROS1 fusions between DNA-based NGS and RNA-based NGS through rigorous validation methods. These inconsistencies were attributed to alternative splicing resulting in out-of-frame or exonic ROS1 fusions. These findings significantly contribute to our understanding of the molecular characteristics of ROS1 fusions, which have implications for panel design and the treatment of NSCLC patients with ROS1 rearrangements.

Detection and Estimation of Change Point in Volatility Function of Foreign Exchange Rate Returns

This work aims at detection and estimation of a change point in conditional variance function of a Nonparametric Auto-Regressive Conditional Heteroscedastic model. The conditional mean and conditional variance functions are not specified a priori but estimated using Nadaraya Watson kernel. This is because inferences based on nonparametric approaches are robust against misspecification of the conditional mean function and the conditional variance function of returns. The squared residuals obtained after estimating the regression function of the returns are used in estimating the conditional variance function. Further, the squared residuals are used in developing a test statistic for unknown abrupt change point in volatility of the exchange rate returns. The test statistic takes into consideration the conditional heteroskedasticity of the disturbances, dependence of the returns, heterogeneity and fourth moment of returns. This does not require prior knowledge of the marginal or the conditional densities of the returns as opposed to maximum likelihood estimation methods. The estimator for change point is considered as the augmented maximum of the test statistic. The consistency of the estimator is stated as a theorem. The asymptotic distribution associated with the test for unknown break points is the Bessel process distribution. The Bessel process distributions have no known simple closed-form expression for the distribution function which makes it difficult to compute exact p-values. Also, the Bessel process distributions depend on two parameters which makes it hard to tabulate the critical values hence one needs to simulate them. After simulating the critical values, hypothesis testing is done in the presence and absence of a change point in volatility of a simulated time series and the test is shown to reject the null hypothesis in the presence of a change point at alpha level of significance. Further, the test fails to reject the null hypothesis in the absence of a change point at alpha level of significance. An application to United States Dollar/Kenya Shilling historical exchange rates returns is made from 1^st January 2010 to 27^th November 2020 where the sample size n = 2839 is done. Through binary segmentation method, three change points are detected, estimated and accounted for. A significant improvement in describing a time series is expected if a point in time for volatility change has been detected and estimated.

Has international CPI inflation comovement strengthened since the global financial crisis?

AbstractThis study detects a structural break in international consumer price index (CPI) inflation comovement. We estimate the dynamic common factor models with unknown breakpoints of cross-country inflation rates and global price index of all commodities. We identify two global factors from the models: a commodity global factor and a noncommodity global factor. The former is a common factor between national inflation rates and commodity price index growth; the latter is a common factor among national inflation rates. The estimation of 29 countries’ quarterly CPI inflation data from 2001:Q1 to 2018:Q2 shows a one-time break in cross-country inflation dynamics in 2008:Q4. Thereafter, the importance of global factors in explaining the national inflation rates is remarkably increased. Furthermore, the increased global inflation synchronization is mainly driven by the larger role of the noncommodity global factor rather than that of the commodity global factor.

Breaks in persistence in fixed-[formula omitted] panel data

This paper considers an autoregressive panel data model in which the autoregressive coefficient has undergone a structural break. The object of interest is the unknown breakpoint. A least squares-based estimator is proposed that is shown to be consistent when only the number of cross-section units, N, is large and the number of time periods, T, is small, thereby enabling quick detection of the onset of a new regime.

Petroleum and Food Sectors Lost Stock Returns against Investments in PSX

The impact of exchange rate exposure and market return on stock returns of petroleum and food sectors PSX listed firms has been investigated empirically. Two econometric models formulated based on the Jorion approach of the two-factor model have been analyzed for petroleum and food sectors stock returns, market return and exchange rate (i.e., USD) for the study period 2005-2012, which represent an era of military regime proceeded by the democratic government of Pakistan Peoples Party. A sample of 37 petroleum and food sectors listed firms have been evaluated by applying the unit root test and OLS multiple regression. Further, the Quandt-Andrews test of unknown breakpoint has been applied, which showed an extended structural break during the period 2007 to 2010. Additionally, the results revealed that the coefficients of exchange rate and market return are negatively related to petroleum and food sectors stock returns. Therefore, investors must take precautions before investing funds in stocks of food and petroleum sector firms.

Comparison of four next generation sequencing platforms for fusion detection: Oncomine by ThermoFisher, AmpliSeq by illumina, FusionPlex by ArcherDX, and QIAseq by QIAGEN

As fusion detection NGS techniques are adopted by clinical labs, assay performance comparison is urgently needed. We compared four fusion-detection assay platforms on a pilot cohort of 24 prostate cancer samples: (1) Oncomine Comprehensive panel v3; (2) AmpliSeq comprehensive panel v3; (3) The solid tumor panel of FusionPlex; and (4) The human oncology panel of QIAseq. The assays were compared for the detection of different types of fusion based on whether the partner gene or the breakpoints are known. All assays detected fusion with known gene partners and known breakpoint, represented by TMPRSS2-ERG. A fusion with known partners but unknown breakpoint, TMPRSS2-ETV4, was reported by OCAv3 and FusionPlex, but not by AICv3 because the specific breakpoint was not in the manifest, nor by QIAseq since the panel did not target the exact exons involved. For fusion with unknown partners, FusionPlex identified the largest number of ETV1 fusions because it had the highest exon coverage for ETV1. Among these, SNRPN-ETV1 and MALAT1-ETV1, were novel findings. To determine reportability of low-level calls of highly prevalent fusions, such as TMPRSS2-ERG, we propose the use of percent fusion reads over total number of reads per sample instead of the fusion read count.

Threshold Research on the Elderly Pedestrian Ratio in Pedestrian Crossing Speed Setting on Signalized Crosswalks in China

Inadequate consideration of the elderly people crossing demand on the signalized intersections would bring great potential safety hazards, especially the speed through the crosswalk. By observing the pedestrian walking speed at three signalized crosswalks and a relatively spacious sidewalk in Chongqing, China, this paper has obtained the walking speed values of 658 elderly people and 1,176 adults at the signalized crosswalks, as well as the walking speed parameters of 868 adults and 422 elderly people on a relatively spacious sidewalk section. Comparing the walking speed of adults walking along the sidewalk section and on signalized crosswalks, the data show that there is no significant difference between these two site speeds. Similarly, when comparing the two site data of the elderly, it is found that their walking speed at the signalized crosswalk is significantly higher than that on the sidewalk section. That is to say, the speed setting for the old people crossing the crosswalk has not been fully considered. Subsequently, taking the elderly’s walking speed as input parameter, establishing the simulation models under different proportions of the elderly and different pedestrian flows, and then gain the walking speed values of the pedestrians with different quantities and different proportion of the elderly pedestrians. With the help of the unknown breakpoint Regression method, under the setting of the elderly pedestrian speed crossing the street, the proportion threshold of the elderly crossing the street at the signalized intersection is obtained. The results show that when the proportion of the elderly is more than 15% of the pedestrians crossing the street, the pedestrian crossing speed value for the signal time is suggested to be 0.97 m/s.

A piecewise model for two-phase growth phenomena

In this paper, we introduce a nonlinear model which can be used as a regression model for modeling phenomena requiring a two-phase growth curves. The proposed model is defined as a continuous piecewise combination of two exponential functions with an unknown break point. Numerical results on real and simulated data sets are presented to illustrate the applicability and the utility of the proposed model on growth data.

Identification of the plateau in maximal oxygen consumption: proposal and application of a new method of analysis

Objective: The classic criterion for VO2máx plateau identification was proposed by Taylor et al. (1955), however, there are many critiques of this method. In this paper, we propose a new statistic-based VO2max plateau identification methodology. In addition, we aim to test for eventual differences between characteristics of the individuals who presented and those who did not present the maximum VO2max plateau.
 Method: Forty-one (n = 41) physically active men participated. The subjects underwent a cardiopulmonary exercise test using ramp protocol to measure the VO2max and other physiological variables. The identification of VO2max plateau was performed by segmented linear regression with unknown breakpoints for each individual.
 Results: Although 58.54% (24) of the sample presented VO2max plateau, no significant differences were observed in metabolic, ventilatory and velocity variables between the groups.
 Conclusion: The methodology presents advantages, since it is adequate to analyze VO2 variations individually and because it is based on statistical techniques, which considers the continuous records of the maximal effort test, not segmenting it in sections for analysis. The comparison between groups, according to the occurrence of the plateau, showed no differences between them.

Testing for cointegration with threshold adjustment in the presence of structural breaks

Abstract In this paper, we develop new threshold cointegration tests with SETAR and MTAR adjustment allowing for the presence of structural breaks in the equilibrium equation. We propose a simple procedure to simultaneously estimate the previously unknown breakpoint and test the null hypothesis of no cointegration. Thereby, we extend the well-known residual-based cointegration test with regime shift introduced by (Gregory, A. W., and B. E. Hansen. 1996a. “Residual-based Tests for Cointegration in Models with Regime Shifts.” Journal of Econometrics 70: 99–126) to include forms of nonlinear adjustment. We derive the asymptotic distribution of the test statistics and demonstrate the finite-sample performance of the tests in a series of Monte Carlo experiments. We find a substantial decrease of power of the conventional threshold cointegration tests caused by a shift in the slope coefficient of the equilibrium equation. The proposed tests perform superior in these situations. An application to the “rockets and feathers” hypothesis of price adjustment in the US gasoline market provides empirical support for this methodology.

Common Breaks in Means for Cross‐Correlated Fixed‐T Panel Data

This note considers a panel data model in which the variable of interest has undergone a common structural break in the mean. The object of interest is the unknown breakpoint. The challenge is to device an estimator that is consistent when the data are cross‐correlated and the number of time periods T is fixed and cannot be increased without bound. The proposed solution involves taking an already existing estimator initially proposed for cross‐section uncorrelated panels and applying it to defactored data. Consistency is established as the number of cross‐section units N grows large, and is verified in small samples using Monte Carlo simulation.

Identification of a Novel 9.7 kb Deletion Causing α0-Thalassemia in Two Pregnant Women in Southern China

The technique of combining multiplex ligation-dependent probe amplification (MLPA), array comparative genomic hybridization (CGH) and gap-polymerase chain reaction (gap-PCR) is an effective way to locate unknown breakpoints on the α-globin genes. In the current report, a novel deletion was detected in two pregnant women with moderate hematological phenotypes. Multiplex ligation-dependent probe amplification and array CGH revealed a probable 9.7 kb deletion at 16p13.3. The breakpoints were precisely defined by gap-PCR and direct sequencing. This deletion (NG_000006.1: g.32709_42418del) included HBA1, HBA2 and HBQ, which resulted in an α0-thalassemia (α0-thal) mutation. There would be a 25.0% chance of conceiving an α-thal intermedia or α-thal major (α-TI or α-TM) fetus if the couples are both carriers. Rare large deletions can cause α-thalassemia (α-thal) and the structure analysis of an unknown deletion is important for clinical diagnosis and further genetic counseling.

Nonparametric testing for smooth structural changes in panel data models

Detecting and modeling structural changes in time series models have attracted great attention. However, relatively little effort has been paid to the testing of structural changes in panel data models despite their increasing importance in economics and finance. In this paper, we propose a new approach to testing structural changes in panel data models. Unlike the bulk of the literature on structural changes, which focuses on detection of abrupt structural changes, we consider smooth structural changes for which model parameters are unknown deterministic smooth functions of time except for a finite number of time points. We use nonparametric local smoothing method to consistently estimate the smooth changing parameters and develop two consistent tests for smooth structural changes in panel data models. The first test is to check whether all model parameters are stable over time. The second test is to check potential time-varying interaction while allowing for a common trend. Both tests have an asymptotic N(0,1) distribution under the null hypothesis of parameter constancy and are consistent against a vast class of smooth structural changes as well as abrupt structural breaks with possibly unknown break points alternatives. Simulation studies show that the tests provide reliable inference in finite samples and two empirical examples with respect to a cross-country growth model and a capital structure model are discussed.

A pruned recursive solution to the multiple change point problem

Long time series are often heterogeneous in nature. As such, the most appropriate model is one whose parameters are allowed to change through time. The exponential number of solutions to the multiple change point problem requires an efficient algorithm in order to be computationally feasible. Exact Bayesian solutions have at best quadratic complexity in the number of observations, which still can be too slow for very large data sets. Here, a pruned dynamic programming algorithm is proposed to fit a piecewise regression model with unknown break points to a data set. The algorithm removes unessential calculations, reducing the complexity of the most time consuming step of the algorithm from quadratic in the number of observations to quadratic in the average distance between change points. A distance measure is introduced that can be used to determine the divergence of the approximate joint posterior distribution from the exact posterior distribution. Analysis of two real data sets shows that this approximate algorithm produces a nearly identical representation of the joint posterior distribution on the locations of the change points, but with a significantly faster run time than its exact counterpart.

Detecting structural change with heteroskedasticity

ABSTRACTThe hypothesis of structural stability that the regression coefficients do not change over time is central to all applications of linear regression models. It is rather surprising that existing theory as well as practice focus on testing for structural change under homoskedasticity – that is, regression coefficients may change, but the variances remain the same. Since structural change can, and often does, involve changes in variances, this is a puzzling gap in the literature. Our main focus in this paper is to utilize a newly developed test (MZ) by Maasoumi et al. (2010) that tests simultaneously for break in regression coefficients as well as in variance. Currently, the sup F test is most widely used for structural change. This has certain optimality properties shown by Andrews (1993). However, this test assumes homoskedasticity across the structural change. We introduce the sup MZ test which caters to unknown breakpoints, and also compare it to the sup F. Our Monte Carlo results show that sup MZ test incurs only a low cost in case of homoskedasticity while having hugely better performance in case of heteroskedasticity. The simulation results are further supported by providing a real-world application. In real-world datasets, we find that structural change often involves heteroskedasticity. In such cases, the sup F test can fail to detect structural breaks and give misleading results, while the sup MZ test works well. We conclude that the sup MZ test is superior to current methodology for detecting structural change.

Taxable Capacity, Tax Efforts and Structural Break: Do the Child States Follow Their Respective Parents?

The present article makes an attempt to test the hypothesis whether smaller states have better fiscal efficiency in terms of own tax revenue collections or not. This has been tested by taking the case of three states Uttar Pradesh, Madhya Pradesh and Bihar with their child states Uttarakhand, Chhattisgarh and Jharkhand, respectively. For this purpose tax buoyancy, tax capacity and efforts, and structural break models—Chow test (with known break points) and Quandt likelihood ratio (QLR) test (with unknown break points), to see the impact of value added tax (VAT) on own tax revenue (OTR)—have been estimated. Log-log regression model was adopted for both calculating tax buoyancies and taxable capacity of each parent and child state. However, we did not find any conclusive evidence that child states have better tax buoyancy or tax efforts. On the basis of our observations, we concluded that the size of the state is not a major determinant affecting revenue efficiency of the state. Other supplementary policies like efficient tax administration, developed industrial sector, reduced exemptions and concessions, broad-based and effective tax rates are equally important. JEL Classification: H11, H21, H71, R50

The dynamics of the relative global sector effects and contagion in emerging markets equity returns

The paper decomposes the variance of emerging market equity returns to the global market and country specific constituents. The global component is then scaled by the country specific component to determine the relative global sector influence in country equity returns. Additionally, the paper explores contagion by testing for significant shifts in the BEKK-correlations between the emerging markets and the world market around the identified structural breakpints in crisis periods. Using the Quandt test of unknown breakpoint, evidence is provided of significant structural breaks in the relative global effects in all of the markets. Additionally, the identified structural breaks mostly correspond to global effects particularly the 2008 global financial crisis (GFC) and the 2007 global oil shocks (GOS) that heralded the GFC. The findings show that the global effects are time-varying, and that the GFC or GOS led to significant surge in the relative global influence in the emerging markets returns. The evidence indicates a reversion in the rate of change of the global effects to around the pre-GFC or pre-GOs level for all of the markets; however, there is no reversion in the global effects. This suggests that the increase in the global effects resulting from the GFC or the GOS may be permanent. Additionally, the findings infer contagion from the world to the emerging markets around the GFC.