When One Size Does Not Fit All: A Simple Statistical Method to Deal with Across-Individual Variations of Effects

In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability). In such paradoxical situations, statistical tools are at odds with the researcher’s aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30–50 individuals) suggest it as a tool of choice in exploratory studies

Genome-Wide Expression Analysis Identifies a Modulator of Ionizing Radiation-Induced p53-Independent Apoptosis in Drosophila melanogaster

Tumor suppressor p53 plays a key role in DNA damage responses in metazoa, yet more than half of human tumors show p53 deficiencies. Therefore, understanding how therapeutic genotoxins such as ionizing radiation (IR) can elicit DNA damage responses in a p53-independent manner is of clinical importance. Drosophila has been a good model to study the effects of IR because DNA damage responses as well as underlying genes are conserved in this model, and because streamlined gene families make loss-of-function analyses feasible. Indeed, Drosophila is the only genetically tractable model for IR-induced, p53-independent apoptosis and for tissue regeneration and homeostasis after radiation damage. While these phenomenon occur only in the larvae, all genome-wide gene expression analyses after irradiation to date have been in embryos. We report here the first analysis of IR-induced, genome-wide gene expression changes in wild type and p53 mutant Drosophila larvae. Key data from microarrays were confirmed by quantitative RT-PCR. The results solidify the central role of p53 in IR-induced transcriptome changes, but also show that nearly all changes are made of both p53-dependent and p53-independent components. p53 is found to be necessary not just for the induction of but also for the repression of transcript levels for many genes in response to IR. Furthermore, Functional analysis of one of the top-changing genes, EF1a-100E, implicates it in repression of IR-induced p53-independent apoptosis. These and other results support the emerging notion that there is not a single dominant mechanism but that both positive and negative inputs collaborate to induce p53-independent apoptosis in response to IR in Drosophila larvae

Chk2 and p53 Are Haploinsufficient with Dependent and Independent Functions to Eliminate Cells after Telomere Loss

The mechanisms that cells use to monitor telomere integrity, and the array of responses that may be induced, are not fully defined. To date there have been no studies in animals describing the ability of cells to survive and contribute to adult organs following telomere loss. We developed assays to monitor the ability of somatic cells to proliferate and differentiate after telomere loss. Here we show that p53 and Chk2 limit the growth and differentiation of cells that lose a telomere. Furthermore, our results show that two copies of the genes encoding p53 and Chk2 are required for the cell to mount a rapid wildtype response to a missing telomere. Finally, our results show that, while Chk2 functions by activating the p53-dependent apoptotic cascade, Chk2 also functions independently of p53 to limit survival. In spite of these mechanisms to eliminate cells that have lost a telomere, we find that such cells can make a substantial contribution to differentiated adult tissues

Systematic Review of the Relationship Between Autism Stigma and Informal Caregiver Mental Health

Families play a crucial role in determining the mental health of the autistic individual(s) they are caring for. However, the stigma associated with autism can impair caregiver health. To investigate this, empirical evidence pertaining to stigma’s impact on informal caregivers’ mental health was systematically reviewed. All twelve included studies (n = 1442 informal caregivers) consistently reported the impact of autism related stigma upon caregiver mental health to be significant, meaningful and complex. A new theoretical framework describing the relationship between stigma and caregiver mental health is constructed. Moderating variables include those both changeable through intervention (e.g. hopelessness, self-esteem, self-compassion) and not changeable (gender, culture, financial burden and time since diagnosis). Implications and recommendations for professionals, interventions and future research are proposed

An Iterative Jackknife Approach for Assessing Reliability and Power of fMRI Group Analyses

For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20–27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a “dual-use” fMRI task, n = 39), and the implications of this approach are discussed

Biofluid Biomarkers in Huntington's Disease

Huntington's disease (HD) is a chronic progressive neurodegenerative condition where new markers of disease progression are needed. So far no disease-modifying interventions have been found, and few interventions have been proven to alleviate symptoms. This may be partially explained by the lack of reliable indicators of disease severity, progression, and phenotype.Biofluid biomarkers may bring advantages in addition to clinical measures, such as reliability, reproducibility, price, accuracy, and direct quantification of pathobiological processes at the molecular level; and in addition to empowering clinical trials, they have the potential to generate useful hypotheses for new drug development.In this chapter we review biofluid biomarker reports in HD, emphasizing those we feel are likely to be closest to clinical applicability

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

A validated UPLC–MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9 min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6 ng/L of original sample. Intra- and inter-day precision analysis showed relative standard deviations (RSD) of 1.2–9.6% and 1.3–12.0% respectively. The method was applied to the analysis of aquatic samples (n = 206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n = 22), cylindrospermopsin (n = 25), microcystin-RR (n = 17), micro- cystin-LR (n = 12), microcystin-LY (n = 1), microcystin-LF (n = 1) and nodularin (n = 5). For microcystins, the levels detected ranged from 0.001 to 1.51 mg/L, with two samples showing combined levels above the guideline set by the WHO of 1 mg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure