Systems analysis and controlled malaria infection in Europeans and Africans elucidate naturally acquired immunity.

Controlled human infections provide opportunities to study the interaction between the immune system and malaria parasites, which is essential for vaccine development. Here, we compared immune signatures of malaria-naive Europeans and of Africans with lifelong malaria exposure using mass cytometry, RNA sequencing and data integration, before and 5 and 11 days after venous inoculation with Plasmodium falciparum sporozoites. We observed differences in immune cell populations, antigen-specific responses and gene expression profiles between Europeans and Africans and among Africans with differing degrees of immunity. Before inoculation, an activated/differentiated state of both innate and adaptive cells, including elevated CD161+CD4+ T cells and interferon-γ production, predicted Africans capable of controlling parasitemia. After inoculation, the rapidity of the transcriptional response and clusters of CD4+ T cells, plasmacytoid dendritic cells and innate T cells were among the features distinguishing Africans capable of controlling parasitemia from susceptible individuals. These findings can guide the development of a vaccine effective in malaria-endemic regions.

NetTDP: permutation-based true discovery proportions for differential co-expression network analysis.

Existing methods for differential network analysis could only infer whether two networks of interest have differences between two groups of samples, but could not quantify and localize network differences. In this work, a novel method, permutation-based Network True Discovery Proportions (NetTDP), is proposed to quantify the number of edges (correlations) or nodes (genes) for which the co-expression networks are different. In the NetTDP method, we propose an edge-level statistic and a node-level statistic, and detect true discoveries of edges and nodes in the sense of differential co-expression network, respectively, by the permutation-based sumSome method. Furthermore, the NetTDP method could further localize the differences by inferring the TDPs for edge or gene subsets of interest, which can be selected post hoc. Our NetTDP method allows inference on data-driven modules or biology-driven gene sets, and remains valid even when these sub-networks are optimized using the same data. Experimental results on both simulation data sets and five real data sets show the effectiveness of the proposed method in inferring the quantification and localization of differential co-expression networks. The R code is available at https://github.com/LiminLi-xjtu/NetTDP.

Cerebrospinal Fluid and Plasma Amine Profiles in Interictal Migraine.

OBJECTIVE: Impaired amine metabolism has been associated with the etiology of migraine, that is, why patients continue to get migraine attacks. However, evidence from cerebrospinal fluid (CSF) is lacking. Here, we evaluated individual amine levels, global amine profiles, and amine pathways in CSF and plasma of interictal migraine patients and healthy controls. METHODS: CSF and plasma were sampled between 8:30 am and 1:00 pm, randomly and interchangeably over the time span to avoid any diurnal and seasonal influences, from healthy volunteers and interictal migraine patients, matched for age, sex, and sampling time. The study was approved by the local medical ethics committee. Individual amines (n = 31), global amine profiles, and specific amine pathways were analyzed using a validated ultraperformance liquid chromatography mass spectrometry platform. RESULTS: We analyzed n = 99 participants with migraine with aura, n = 98 with migraine without aura, and n = 96 healthy volunteers. Univariate analysis with Bonferroni correction indicated that CSF L-arginine was reduced in migraine with aura (10.4%, p < 0.001) and without aura (5.0%, p = 0.03). False discovery rate-corrected CSF L-phenylalanine was also lower in migraine with aura (6.9%, p = 0.011) and without aura (8.1%, p = 0.001), p = 0.088 after Bonferroni correction. Multivariate analysis revealed that CSF global amine profiles were similar for both types of migraine (p = 0.64), but distinct from controls (p = 0.009). Global profile analyses were similar in plasma. The strongest associated pathways with migraine were related to L-arginine metabolism. INTERPRETATION: L-Arginine was decreased in the CSF (but not in plasma) of interictal patients with migraine with or without aura, and associated pathways were altered. This suggests that dysfunction of nitric oxide signaling is involved in susceptibility to getting migraine attacks. ANN NEUROL 2023;93:715-728.

Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data.

BACKGROUND: There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual's true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of one's chronological age-independent aging divergence ∆. METHODS: We investigated the statistical assumptions underlying the most popular cross-sectional biological age predictors, based on multiple linear regression, the Klemera-Doubal method or principal component analysis. We used synthetic and real data to illustrate the consequences if this assumption does not hold. RESULTS: The most popular cross-sectional biological age predictors all use the same strong underlying assumption, namely that a candidate marker of aging's association with chronological age is directly informative of its association with the aging rate ∆. We called this the identical-association assumption and proved that it is untestable in a cross-sectional setting. If this assumption does not hold, weights assigned to candidate markers of aging are uninformative, and no more signal may be captured than if markers would have been assigned weights at random. CONCLUSIONS: Cross-sectional methods for predicting biological age commonly use the untestable identical-association assumption, which previous literature in the field had never explicitly acknowledged. These methods have inherent limitations and may provide uninformative results, highlighting the importance of researchers exercising caution in the development and interpretation of cross-sectional biological age predictors.

Early-Onset Sepsis as an Early Predictor for Retinopathy of Prematurity: A Meta-analysis.

OBJECTIVE: Neonatal sepsis has been established as a risk factor for retinopathy of prematurity (ROP) but previous meta-analyses have predominately focused on late-onset sepsis (LOS). This meta-analysis aims to explore the association between early-onset sepsis (EOS) and the risk of ROP. STUDY DESIGN: Observational studies reporting (unadjusted) data on proven EOS in neonates with ROP were included. PubMed, Embase, and Cochrane Library were searched. Proven EOS was defined as a positive blood or cerebrospinal fluid culture. Effect sizes were calculated by using logistic random-effects models and meta-regression analyses. Primary outcomes were any stage ROP and severe ROP (≥stage 3, type I, aggressive [posterior] ROP, plus disease or requiring treatment). Potential confounders explored were gestational age at birth, birth weight, small for gestational age, maternal steroid use, necrotizing enterocolitis, LOS, and mechanical ventilation duration. RESULTS: Seventeen studies reporting the incidence of proven EOS in neonates with ROP were included. Proven EOS showed no significant association with any stage ROP (odds ratio [OR] = 1.90; 95% confidence interval [CI]: 0.96-3.79, p = 0.067) but heterogeneity between studies was significantly high. Neonates with proven EOS had an increased risk for severe ROP (OR = 2.21; 95% CI: 1.68-2.90), and no significant confounders influencing this effect size were found in the meta-regression analysis. CONCLUSION: Neonates with proven EOS are at increased risk of severe ROP. Neonatologists need to be aware that EOS is an early predictor of ROP and should adapt their policy and treatment decisions where possible to reduce ROP. KEY POINTS: · This meta-analysis reveals a 2.2-fold increased risk of severe ROP in neonates with proven EOS.. · Future studies should distinguish between EOS and LOS when investigating risk factors of ROP.. · Treatment decisions should be adapted where possible in neonates with EOS before ROP screening begins..

Combining Partial True Discovery Guarantee Procedures.

Closed testing has recently been shown to be optimal for simultaneous true discovery proportion control. It is, however, challenging to construct true discovery guarantee procedures in such a way that it focuses power on some feature sets chosen by users based on their specific interest or expertise. We propose a procedure that allows users to target power on prespecified feature sets, that is, "focus sets." Still, the method also allows inference for feature sets chosen post hoc, that is, "nonfocus sets," for which we deduce a true discovery lower confidence bound by interpolation. Our procedure is built from partial true discovery guarantee procedures combined with Holm's procedure and is a conservative shortcut to the closed testing procedure. A simulation study confirms that the statistical power of our method is relatively high for focus sets, at the cost of power for nonfocus sets, as desired. In addition, we investigate its power property for sets with specific structures, for example, trees and directed acyclic graphs. We also compare our method with AdaFilter in the context of replicability analysis. The application of our method is illustrated with a gene ontology analysis in gene expression data.

Inflated false discovery rate due to volcano plots: problem and solutions.

MOTIVATION: Volcano plots are used to select the most interesting discoveries when too many discoveries remain after application of Benjamini-Hochberg's procedure (BH). The volcano plot suggests a double filtering procedure that selects features with both small adjusted $P$-value and large estimated effect size. Despite its popularity, this type of selection overlooks the fact that BH does not guarantee error control over filtered subsets of discoveries. Therefore the selected subset of features may include an inflated number of false discoveries. RESULTS: In this paper, we illustrate the substantially inflated type I error rate of volcano plot selection with simulation experiments and RNA-seq data. In particular, we show that the feature with the largest estimated effect is a very likely false positive result. Next, we investigate two alternative approaches for multiple testing with double filtering that do not inflate the false discovery rate. Our procedure is implemented in an interactive web application and is publicly available.

Closed testing with Globaltest, with application in metabolomics.

The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple feature sets, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the familywise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, that is, the researcher may choose feature sets of interest after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on comprehensive R archive network for the implementation of the shortcut procedure, with applications on several real metabolomics data examples.

Histological Chorioamnionitis and Funisitis as New Risk Factors for Retinopathy of Prematurity: A Meta-analysis.

OBJECTIVE: The role of placental inflammation in neonatal morbidities is underestimated due to lack of placental examination. This meta-analysis aims to assess the association between histological chorioamnionitis (HCA) with and without funisitis (FUN) and risk of retinopathy of prematurity (ROP). STUDY DESIGN: Forty-five studies reporting (unadjusted) data on HCA without FUN and HCA with FUN in neonates with ROP were included. Primary outcomes were any stage ROP and severe ROP. Potential confounders explored were gestational age (GA) at birth, birthweight, maternal steroid use, necrotizing enterocolitis, sepsis (suspected/proven) and mechanical ventilation duration. RESULTS: Neonates with HCA had increased risk for any stage ROP (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.3-2.4) and severe ROP (OR 1.5; 95% CI 1.2-1.8) compared with neonates without HCA. The rates of any stage ROP (OR 1.8; 95% CI 1.4-2.2) and severe ROP (OR 1.4; 95% CI 1.1-1.6) were higher in neonates with FUN compared with neonates without FUN. Multivariate meta-regression analysis suggests that lower GA increases the effect size between FUN and severe ROP. CONCLUSION: This meta-analysis confirms that presence of HCA and FUN are risk factors for any stage ROP and severe ROP. Structured histological placental examination of HCA and FUN may be a tool to further refine the ROP risk profile. KEY POINTS: · This systematic review confirms that HCA is a risk factor for ROP.. · This meta-analysis reveals that FUN results in an even higher risk for developing ROP.. · Placental examination of HCA/FUN may be a tool to further refine the ROP risk profile..

Molecular Landscape of Pelvic Organ Prolapse Provides Insights into Disease Etiology.

Pelvic organ prolapse (POP) represents a major health care burden in women, but its underlying pathophysiological mechanisms have not been elucidated. We first used a case-control design to perform an exome chip study in 526 women with POP and 960 control women to identify single nucleotide variants (SNVs) associated with the disease. We then integrated the functional interactions between the POP candidate proteins derived from the exome chip study and other POP candidate molecules into a molecular landscape. We found significant associations between POP and SNVs in 54 genes. The proteins encoded by 26 of these genes fit into the molecular landscape, together with 43 other POP candidate molecules. The POP landscape is located in and around epithelial cells and fibroblasts of the urogenital tract and harbors four interacting biological processes-epithelial-mesenchymal transition, immune response, modulation of the extracellular matrix, and fibroblast function-that are regulated by sex hormones and TGFB1. Our findings were corroborated by enrichment analyses of differential gene expression data from an independent POP cohort. Lastly, based on the landscape and using vaginal fibroblasts from women with POP, we predicted and showed that metformin alters gene expression in these fibroblasts in a beneficial direction. In conclusion, our integrated molecular landscape of POP provides insights into the biological processes underlying the disease and clues towards novel treatments.

Better-than-chance classification for signal detection.

The estimated accuracy of a classifier is a random quantity with variability. A common practice in supervised machine learning, is thus to test if the estimated accuracy is significantly better than chance level. This method of signal detection is particularly popular in neuroimaging and genetics. We provide evidence that using a classifier's accuracy as a test statistic can be an underpowered strategy for finding differences between populations, compared to a bona fide statistical test. It is also computationally more demanding than a statistical test. Via simulation, we compare test statistics that are based on classification accuracy, to others based on multivariate test statistics. We find that the probability of detecting differences between two distributions is lower for accuracy-based statistics. We examine several candidate causes for the low power of accuracy-tests. These causes include: the discrete nature of the accuracy-test statistic, the type of signal accuracy-tests are designed to detect, their inefficient use of the data, and their suboptimal regularization. When the purpose of the analysis is the evaluation of a particular classifier, not signal detection, we suggest several improvements to increase power. In particular, to replace V-fold cross-validation with the Leave-One-Out Bootstrap.

Echo planar imaging-induced errors in intracardiac 4D flow MRI quantification.

PURPOSE: To assess errors associated with EPI-accelerated intracardiac 4D flow MRI (4DEPI) with EPI factor 5, compared with non-EPI gradient echo (4DGRE). METHODS: Three 3T MRI experiments were performed comparing 4DEPI to 4DGRE: steady flow through straight tubes, pulsatile flow in a left-ventricle phantom, and intracardiac flow in 10 healthy volunteers. For each experiment, 4DEPI was repeated with readout and blip phase-encoding gradient in different orientations, parallel or perpendicular to the flow direction. In vitro flow rates were compared with timed volumetric collection. In the left-ventricle phantom and in vivo, voxel-based speed and spatio-temporal median speed were compared between sequences, as well as mitral and aortic transvalvular net forward volume. RESULTS: In steady-flow phantoms, the flow rate error was largest (12%) for high velocity (>2 m/s) with 4DEPI readout gradient parallel to the flow. Voxel-based speed and median speed in the left-ventricle phantom were ≤5.5% different between sequences. In vivo, mean net forward volume inconsistency was largest (6.4 ± 8.5%) for 4DEPI with nonblip phase-encoding gradient parallel to the main flow. The difference in median speed for 4DEPI versus 4DGRE was largest (9%) when the 4DEPI readout gradient was parallel to the flow. CONCLUSIONS: Velocity and flow rate are inaccurate for 4DEPI with EPI factor 5 when flow is parallel to the readout or blip phase-encoding gradient. However, mean differences in flow rate, voxel-based speed, and spatio-temporal median speed were acceptable (≤10%) when comparing 4DEPI to 4DGRE for intracardiac flow in healthy volunteers.

Simultaneous confidence intervals for ranks with application to ranking institutions.

When a ranking of institutions such as medical centers or universities is based on a numerical measure of performance provided with a standard error, confidence intervals (CIs) should be calculated to assess the uncertainty of these ranks. We present a novel method based on Tukey's honest significant difference test to construct simultaneous CIs for the true ranks. When all the true performances are equal, the probability of coverage of our method attains the nominal level. In case the true performance measures have no exact ties, our method is conservative. For this situation, we propose a rescaling method to the nominal level that results in shorter CIs while keeping control of the simultaneous coverage. We also show that a similar rescaling can be applied to correct a recently proposed Monte-Carlo based method, which is anticonservative. After rescaling, the two methods perform very similarly. However, the rescaling of the Monte-Carlo based method is computationally much more demanding and becomes infeasible when the number of institutions is larger than 30-50. We discuss another recently proposed method similar to ours based on simultaneous CIs for the true performance. We show that our method provides uniformly shorter CIs for the same confidence level. We illustrate the superiority of our new methods with a data analysis for travel time to work in the United States and on rankings of 64 hospitals in the Netherlands.

Gaining power in multiple testing of interval hypotheses via conditionalization.

In this article, we introduce a novel procedure for improving power of multiple testing procedures (MTPs) of interval hypotheses. When testing interval hypotheses the null hypothesis $P$-values tend to be stochastically larger than standard uniform if the true parameter is in the interior of the null hypothesis. The new procedure starts with a set of $P$-values and discards those with values above a certain pre-selected threshold, while the rest are corrected (scaled-up) by the value of the threshold. Subsequently, a chosen family-wise error rate (FWER) or false discovery rate MTP is applied to the set of corrected $P$-values only. We prove the general validity of this procedure under independence of $P$-values, and for the special case of the Bonferroni method, we formulate several sufficient conditions for the control of the FWER. It is demonstrated that this "filtering" of $P$-values can yield considerable gains of power.

Longitudinal changes in cerebral white matter microstructure in newly diagnosed systemic lupus erythematosus patients.

OBJECTIVES: To evaluate longitudinal variations in diffusion tensor imaging (DTI) metrics of different white matter (WM) tracts of newly diagnosed SLE patients, and to assess whether DTI changes relate to changes in clinical characteristics over time. METHODS: A total of 17 newly diagnosed SLE patients (19-55 years) were assessed within 24 months from diagnosis with brain MRI (1.5 T Philips Achieva) at baseline, and after at least 12 months. Fractional anisotropy, mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity values were calculated in several normal-appearing WM tracts. Longitudinal variations in DTI metrics were analysed by repeated measures analysis of variance. DTI changes were separately assessed for 21 WM tracts. Associations between longitudinal alterations of DTI metrics and clinical variables (SLEDAI-2K, complement levels, glucocorticoid dosage) were evaluated using adjusted Spearman correlation analysis. RESULTS: Mean MD and RD values from the normal-appearing WM significantly increased over time (P = 0.019 and P = 0.021, respectively). A significant increase in RD (P = 0.005) and MD (P = 0.012) was found in the left posterior limb of the internal capsule; RD significantly increased in the left retro-lenticular part of the internal capsule (P = 0.013), and fractional anisotropy significantly decreased in the left corticospinal tract (P = 0.029). No significant correlation was found between the longitudinal change in DTI metrics and the change in clinical measures. CONCLUSION: Increase in diffusivity, reflecting a compromised WM tissue microstructure, starts in initial phases of the SLE disease course, even in the absence of overt neuropsychiatric (NP) symptoms. These results indicate the importance of monitoring NP involvement in SLE, even shortly after diagnosis.

Pathway testing for longitudinal metabolomics.

We propose a top-down approach for pathway analysis of longitudinal metabolite data. We apply a score test based on a shared latent process mixed model which can identify pathways with differentially progressing metabolites. The strength of our approach is that it can handle unbalanced designs, deals with potential missing values in the longitudinal markers, and gives valid results even with small sample sizes. Contrary to bottom-up approaches, correlations between metabolites are explicitly modeled leveraging power gains. For large pathway sizes, a computationally efficient solution is proposed based on pseudo-likelihood methodology. We demonstrate the advantages of the proposed method in identification of differentially expressed pathways through simulation studies. Finally, longitudinal metabolite data from a mice experiment is analyzed to demonstrate our methodology.

What (not) to expect when classifying rare events.

When building classifiers, it is natural to require that the classifier correctly estimates the event probability (Constraint 1), that it has equal sensitivity and specificity (Constraint 2) or that it has equal positive and negative predictive values (Constraint 3). We prove that in the balanced case, where there is equal proportion of events and non-events, any classifier that satisfies one of these constraints will always satisfy all. Such unbiasedness of events and non-events is much more difficult to achieve in the case of rare events, i.e. the situation in which the proportion of events is (much) smaller than 0.5. Here, we prove that it is impossible to meet all three constraints unless the classifier achieves perfect predictions. Any non-perfect classifier can only satisfy at most one constraint, and satisfying one constraint implies violating the other two constraints in a specific direction. Our results have implications for classifiers optimized using g-means or F1-measure, which tend to satisfy Constraints 2 and 1, respectively. Our results are derived from basic probability theory and illustrated with simulations based on some frequently used classifiers.

Incomplete Excision of Cutaneous Squamous Cell Carcinoma; Systematic Review of the Literature.

The treatment of choice for cutaneous squamous cell carcinoma is complete surgical excision. Incomplete excision of cutaneous squamous cell carcinoma has an increased risk of local recurrence, deep subclinical progression, and metastasis. This study aimed to investigate the proportion and risk factors of incomplete excised cutaneous squamous cell carcinoma. A systematic review of the literature was performed. Incomplete excision rates for cutaneous squamous cell carcinoma ranged from 0.4% to 35.7%. The pooled incomplete excision risk estimate was 13% (95% confidence interval 9-17%). Risk factors noted in more than one study for incomplete excision included tumor depth and size, type of operator, head and neck localization, and former incomplete excision. We found an overall incomplete excision rate of 13% for cutaneous squamous cell carcinoma. Risk factors should be taken into account in the management of cutaneous squamous cell carcinoma surgical treatment.

A test for detecting differential indirect trans effects between two groups of samples.

Integrative analysis of copy number and gene expression data can help in understanding the cis and trans effect of copy number aberrations on transcription levels of genes involved in a pathway. To analyse how these copy number mediated gene-gene interactions differ between groups of samples we propose a new method, named dNET. Our method uses ridge regression to model the network topology involving one gene's expression level, its gene dosage and the expression levels of other genes in the network. The interaction parameters are estimated by fitting the model per gene for all samples together. However, instead of testing for differential network topology per gene, dNET tests for an overall difference in estimated parameters between two groups of samples and produces a single p-value. With the help of several simulation studies, we show that dNET can detect differential network nodes with high accuracy and low rate of false positives even in the presence of differential cis effects. We also apply dNET to publicly available TCGA cancer datasets and identify pathways where copy number mediated gene-gene interactions differ between samples with cancer stage lower than stage 3 and samples with cancer stage 3 or above.

Tissue-sparing properties of Mohs micrographic surgery for infiltrative basal cell carcinoma.

BACKGROUND: Mohs micrographic surgery (MMS) should lead to tissue sparing of healthy skin compared with standard surgical excision because smaller surgical margins are used. OBJECTIVE: To quantify the tissue-sparing properties of MMS in primary basal cell carcinoma (BCC) with an infiltrative growth pattern. METHODS: A prospective study including 256 primary BCCs with an infiltrative growth pattern was performed. Tumor sizes were measured in 2 perpendicular directions. Surface defect areas after MMS were measured. The suspected defect surface area with standard excision using a 5-mm margin was calculated. The primary outcome of this study was the size of the defect surface area spared with MMS compared with the calculated defect surface area with a standard excision. RESULTS: The median tumor size was 71 mm2, and the median defect size after MMS was 154 mm2. The median defect size calculated for standard surgical excision was 298 mm2. We have shown that MMS of BCC with an infiltrative growth pattern had a 46.4% tissue-sparing effect when compared with standard surgical excision (95% confidence interval, 43.4%-49.1%; P value < .001). LIMITATIONS: Single-center study design. Lack of a randomized control group for ethical reasons. CONCLUSION: A rate of tissue sparing of 46% can be reached by using MMS for primary BCC with an infiltrative growth pattern.