Partial Coherence Estimation via Spectral Matrix Shrinkage under Quadratic Loss

Partial coherence is an important quantity derived from spectral or precision matrices and is used in seismology, meteorology, oceanography, neuroscience and elsewhere. If the number of complex degrees of freedom only slightly exceeds the dimension of the multivariate stationary time series, spectral matrices are poorly conditioned and shrinkage techniques suggest themselves. When true partial coherencies are quite large then for shrinkage estimators of the diagonal weighting kind it is shown empirically that the minimization of risk using quadratic loss (QL) leads to oracle partial coherence estimators superior to those derived by minimizing risk using Hilbert-Schmidt (HS) loss. When true partial coherencies are small the methods behave similarly. We derive two new QL estimators for spectral matrices, and new QL and HS estimators for precision matrices. In addition for the full estimation (non-oracle) case where certain trace expressions must also be estimated, we examine the behaviour of three different QL estimators, the precision matrix one seeming particularly robust and reliable. For the empirical study we carry out exact simulations derived from real EEG data for two individuals, one having large, and the other small, partial coherencies. This ensures our study covers cases of real-world relevance

Random Matrix Derived Shrinkage of Spectral Precision Matrices

Much research has been carried out on shrinkage methods for real-valued covariance matrices. In spectral analysis of $p$-vector-valued time series there is often a need for good shrinkage methods too, most notably when the complex-valued spectral matrix is singular. The equivalent of the Ledoit-Wolf (LW) covariance matrix estimator for spectral matrices can be improved on using a Rao-Blackwell estimator, and using random matrix theory we derive its form. Such estimators can be used to better estimate inverse spectral (precision) matrices too, and a random matrix method has previously been proposed and implemented via extensive simulations. We describe the method, but carry out computations entirely analytically, and suggest a way of selecting an important parameter using a predictive risk approach. We show that both the Rao-Blackwell estimator and the random matrix estimator of the precision matrix can substantially outperform the inverse of the LW estimator in a time series setting. Our new methodology is applied to EEG-derived time series data where it is seen to work well and deliver substantial improvements for precision matrix estimation

p-Value combiners for graphical modelling of EEG data in thefrequency domain

Background: In the graphical modelling of brain data, we are interested in estimating connectivitybetween various regions of interest, and evaluating statistical significance in order to derive a networkmodel. This process involves aggregating results across frequency ranges and several patients, in orderto obtain an overall result that can serve to construct a graph.New method: In this paper, we propose a method based on p-value combiners, which have never beenused in applications to EEG data analysis. This new method is split into two aspects: frequency-wide testsand group-wide tests. The first step can be effectively adjusted to control for false detection rate.Results: This two-step protocol is applied to EEG data collected from distinct groups of mental healthpatients, in order to draw graphical models for each group and highlight structural connectivity differ-ences. Using the method proposed, we show that it is possible to reliably achieve this while effectivelycontrolling for false connections detection.Comparison with existing method(s): Conventionally, the Holm’s Stepdown procedure is used for this typeof problem, as it is robust to type I errors. However, it is known to be conservative and prone to falsenegatives. Furthermore, unlike the proposed methods, it does not directly output a decision rule onwhether to accept or reject a statement.Conclusions: The proposed methodology offers significant improvements over the stepdown procedurein terms of error rate and false negative rate across the network models, as well as in term of applicability

Estimated 24-hour urinary sodium excretion and incident cardiovascular disease and mortality among 398 628 individuals in UK biobank.

We report on an analysis to explore the association between estimated 24-hour urinary sodium excretion (surrogate for sodium intake) and incident cardiovascular disease (CVD) and mortality. Data were obtained from 398 628 UK Biobank prospective cohort study participants (40-69 years) recruited between 2006 and 2010, with no history of CVD, renal disease, diabetes mellitus or cancer, and cardiovascular events and mortality recorded during follow-up. Hazard ratios between 24-hour sodium excretion were estimated from spot urinary sodium concentrations across incident CVD and its components and all-cause and cause-specific mortality. In restricted cubic splines analyses, there was little evidence for an association between estimated 24-hour sodium excretion and CVD, coronary heart disease, or stroke; hazard ratios for CVD (95% CIs) for the 15th and 85th percentiles (2.5 and 4.2 g/day, respectively) compared with the 50th percentile of estimated sodium excretion (3.2 g/day) were 1.05 (1.01-1.10) and 0.96 (0.92-1.00), respectively. An inverse association was observed with heart failure, but that was no longer apparent in sensitivity analysis. A J-shaped association was observed between estimated sodium excretion and mortality. Our findings do not support a J-shaped association of estimated sodium excretion with CVD, although such an association was apparent for all-cause and cause-specific mortality across a wide range of diseases. Reasons for these differences are unclear; methodological limitations, including the use of estimating equations based on spot urinary data, need to be considered in interpreting our findings

Antiretroviral treatment-induced decrease in immune activation contributes to reduced susceptibility to tuberculosis in HIV-1/Mtb co-infected persons

Antiretroviral treatment (ART) reduces the risk of developing active tuberculosis (TB) in HIV-1 co-infected persons. In order to understand host immune responses during ART in the context of Mycobacterium tuberculosis (Mtb) sensitization, we performed RNAseq analysis of whole blood-derived RNA from individuals with latent TB infection coinfected with HIV-1, during the first 6 months of ART. A significant fall in RNA sequence abundance of the Hallmark IFN-alpha, IFN-gamma, IL-6/JAK/STAT3 signaling, and inflammatory response pathway genes indicated reduced immune activation and inflammation at 6 months of ART compared to day 0. Further exploratory evaluation of 65 soluble analytes in plasma confirmed the significant decrease of inflammatory markers after 6 months of ART. Next, we evaluated 30 soluble analytes in QuantiFERON Gold in-tube (QFT) samples from the Ag stimulated and Nil tubes, during the first 6 months of ART in 30 patients. There was a significant decrease in IL-1alpha and IL-1beta (Ag-Nil) concentrations as well as MCP-1 (Nil), supporting decreased immune activation and inflammation. At the same time, IP-10 (Ag-nil) concentrations significantly increased, together with chemokine receptor-expressing CD4 T cell numbers. Our data indicate that ART-induced decrease in immune activation combined with improved antigen responsiveness may contribute to reduced susceptibility to tuberculosis in HIV-1/Mtb co-infected persons

Defective ALC1 nucleosome remodeling confers PARPi sensitization and synthetic lethality with HRD.

Chromatin is a barrier to efficient DNA repair, as it hinders access and processing of certain DNA lesions. ALC1/CHD1L is a nucleosome-remodeling enzyme that responds to DNA damage, but its precise function in DNA repair remains unknown. Here we report that loss of ALC1 confers sensitivity to PARP inhibitors, methyl-methanesulfonate, and uracil misincorporation, which reflects the need to remodel nucleosomes following base excision by DNA glycosylases but prior to handover to APEX1. Using CRISPR screens, we establish that ALC1 loss is synthetic lethal with homologous recombination deficiency (HRD), which we attribute to chromosome instability caused by unrepaired DNA gaps at replication forks. In the absence of ALC1 or APEX1, incomplete processing of BER intermediates results in post-replicative DNA gaps and a critical dependence on HR for repair. Hence, targeting ALC1 alone or as a PARP inhibitor sensitizer could be employed to augment existing therapeutic strategies for HRD cancers

Defective ALC1 nucleosome remodeling confers PARPi sensitization and synthetic lethality with HRD.

Chromatin is a barrier to efficient DNA repair, as it hinders access and processing of certain DNA lesions. ALC1/CHD1L is a nucleosome-remodeling enzyme that responds to DNA damage, but its precise function in DNA repair remains unknown. Here we report that loss of ALC1 confers sensitivity to PARP inhibitors, methyl-methanesulfonate, and uracil misincorporation, which reflects the need to remodel nucleosomes following base excision by DNA glycosylases but prior to handover to APEX1. Using CRISPR screens, we establish that ALC1 loss is synthetic lethal with homologous recombination deficiency (HRD), which we attribute to chromosome instability caused by unrepaired DNA gaps at replication forks. In the absence of ALC1 or APEX1, incomplete processing of BER intermediates results in post-replicative DNA gaps and a critical dependence on HR for repair. Hence, targeting ALC1 alone or as a PARP inhibitor sensitizer could be employed to augment existing therapeutic strategies for HRD cancers

Defective ALC1 nucleosome remodeling confers PARPi sensitization and synthetic lethality with HRD

Chromatin is a barrier to efficient DNA repair, as it hinders access and processing of certain DNA lesions. ALC1/CHD1L is a nucleosome-remodeling enzyme that responds to DNA damage, but its precise function in DNA repair remains unknown. Here we report that loss of ALC1 confers sensitivity to PARP inhibitors, methyl-methanesulfonate, and uracil misincorporation, which reflects the need to remodel nucleosomes following base excision by DNA glycosylases but prior to handover to APEX1. Using CRISPR screens, we establish that ALC1 loss is synthetic lethal with homologous recombination deficiency (HRD), which we attribute to chromosome instability caused by unrepaired DNA gaps at replication forks. In the absence of ALC1 or APEX1, incomplete processing of BER intermediates results in post-replicative DNA gaps and a critical dependence on HR for repair. Hence, targeting ALC1 alone or as a PARP inhibitor sensitizer could be employed to augment existing therapeutic strategies for HRD cancers

Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect

The heart muscle diseases hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure in young, otherwise healthy, individuals. We conducted genome-wide association studies and multi-trait analyses in HCM (1,733 cases), DCM (5,521 cases) and nine left ventricular (LV) traits (19,260 UK Biobank participants with structurally normal hearts). We identified 16 loci associated with HCM, 13 with DCM and 23 with LV traits. We show strong genetic correlations between LV traits and cardiomyopathies, with opposing effects in HCM and DCM. Two-sample Mendelian randomization supports a causal association linking increased LV contractility with HCM risk. A polygenic risk score explains a significant portion of phenotypic variability in carriers of HCM-causing rare variants. Our findings thus provide evidence that polygenic risk score may account for variability in Mendelian diseases. More broadly, we provide insights into how genetic pathways may lead to distinct disorders through opposing genetic effects