Adam Butler

Genomic Classification and Prognosis in Acute Myeloid Leukemia

BACKGROUND Recent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice. METHODS We enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes. RESULTS We identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%); and, provisionally, AML with IDH2(R172) mutations (in 1%). Patients with chromatin-spliceosome and TP53-aneuploidy AML had poor outcomes, with the various class-defining mutations contributing independently and additively to the outcome. In addition to class-defining lesions, other co-occurring driver mutations also had a substantial effect on overall survival. The prognostic effects of individual mutations were often significantly altered by the presence or absence of other driver mutations. Such gene-gene interactions were especially pronounced for NPM1-mutated AML, in which patterns of co-mutation identified groups with a favorable or adverse prognosis. These predictions require validation in prospective clinical trials. CONCLUSIONS The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT00146120.).

Association of a germline copy number polymorphism of APOBEC3A and APOBEC3B with burden of putative APOBEC-dependent mutations in breast cancer

The somatic mutations in a cancer genome are the aggregate outcome of one or more mutational processes operative through the lifetime of the individual with cancer. Each mutational process leaves a characteristic mutational signature determined by the mechanisms of DNA damage and repair that constitute it. A role was recently proposed for the APOBEC family of cytidine deaminases in generating particular genome-wide mutational signatures and a signature of localized hypermutation called kataegis. A germline copy number polymorphism involving APOBEC3A and APOBEC3B, which effectively deletes APOBEC3B, has been associated with modestly increased risk of breast cancer. Here we show that breast cancers in carriers of the deletion show more mutations of the putative APOBEC-dependent genome-wide signatures than cancers in non-carriers. The results suggest that the APOBEC3A-APOBEC3B germline deletion allele confers cancer susceptibility through increased activity of APOBEC-dependent mutational processes, although the mechanism by which this increase in activity occurs remains unknown.

Mutations in ZDHHC9, which encodes a palmitoyltransferase of NRAS and HRAS, cause X-linked mental retardation associated with a marfanoid habitus

We have identified one frameshift mutation, one splice-site mutation, and two missense mutations in highly conserved residues in ZDHHC9 at Xq26.1 in 4 of 250 families with X-linked mental retardation (XLMR). In three of the families, the mental retardation phenotype is associated with a Marfanoid habitus, although none of the affected individuals meets the Ghent criteria for Marfan syndrome. ZDHHC9 is a palmitoyltransferase that catalyzes the posttranslational modification of NRAS and HRAS. The degree of palmitoylation determines the temporal and spatial location of these proteins in the plasma membrane and Golgi complex. The finding of mutations in ZDHHC9 suggests that alterations in the concentrations and cellular distribution of target proteins are sufficient to cause disease. This is the first XLMR gene to be reported that encodes a posttranslational modification enzyme, palmitoyltransferase. Furthermore, now that the first palmitoyltransferase that causes mental retardation has been identified, defects in other palmitoylation transferases become good candidates for causing other mental retardation syndromes.

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Demographic consequences of increased winter births in a large aseasonally breeding mammal (Bos taurus) in response to climate change

1. Studies examining changes in the scheduling of breeding in response to climate change have focused on species with well-defined breeding seasons. Species exhibiting year-round breeding have received little attention and the magnitudes of any responses are unknown. 2. We investigated phenological data for an enclosed feral population of cattle (Bos taurus L.) in northern England exhibiting year-round breeding. This population is relatively free of human interference. 3. We assessed whether the timing of births had changed over the last 60 years, in response to increasing winter and spring temperatures, changes in herd density, and a regime of lime fertilisation. 4. Median birth date became earlier by 1·0 days per year. Analyses of the seasonal distribution of calving dates showed that significantly fewer calves were born in summer (decline from 44% of total births to 20%) and significantly more in winter (increase from 12% to 30%) over the study period. The most pronounced changes occurred in winter, with significant increases in both the proportion and number of births. Winter births arise from conceptions in the previous spring, and we considered models that investigated climate and weather variables associated with the winter preceding and the spring of conceptions. 5. The proportion of winter births was higher when the onset of the plant growing season was earlier during the spring of conceptions. This relationship was much weaker during years when the site had been fertilised with lime, suggesting that increased forage biomass was over-riding the impacts of changing plant phenology. When the onset of the growing season was late, winter births increased with female density. 6. Recruitment estimates from a stage-structured state-space population model were significantly negatively correlated with the proportion of births in the preceding winter, suggesting that calves born in winter are less likely to survive than those born in other seasons. 7. This is one of the first studies to document changes in the phenology of a year-round breeder, suggesting that the impact of climate on the scheduling of biological events may be more extensive than previously thought and that impacts may be negative, even for species with relatively flexible breeding strategies.

Identifying environmental drivers of insect phenology across space and time: Culicoides in Scotland as a case study

Interpreting spatial patterns in the abundance of species over time is a fundamental cornerstone of ecological research. For many species, this type of analysis is hampered by datasets that contain a large proportion of zeros, and data that are overdispersed and spatially autocorrelated. This is particularly true for insects, for which abundance data can fluctuate from zero to many thousands in the space of weeks. Increasingly, an understanding of the ways in which environmental variation drives spatial and temporal patterns in the distribution, abundance and phenology of insects is required for management of pests and vector-borne diseases. In this study, we combine the use of smoothing techniques and generalised linear mixed models to relate environmental drivers to key phenological patterns of two species of biting midges, Culicoides pulicaris and C. impunctatus, of which C. pulicaris has been implicated in transmission of bluetongue in Europe. In so doing, we demonstrate analytical tools for linking the phenology of species with key environmental drivers, despite using a relatively small dataset containing overdispersed and zero-inflated data. We demonstrate the importance of landcover and climatic variables in determining the seasonal abundance of these two vector species, and highlight the need for more empirical data on the effects of temperature and precipitation on the life history traits of palearctic Culicoides spp. in Europe.

Response of lightning NOx emissions and ozone production to climate change : Insights from the Atmospheric Chemistry and Climate Model Intercomparison Project

Results from an ensemble of models are used to investigate the response of lightning nitrogen oxide emissions to climate change and the consequent impacts on ozone production. Most models generate lightning using a parameterization based on cloud top height. With this approach and a present-day global emission of 5 TgN, we estimate a linear response with respect to changes in global surface temperature of +0.44 ± 0.05 TgN K-1. However, two models using alternative approaches give +0.14 and −0.55 TgN K-1 suggesting that the simulated response is highly dependent on lightning parameterization. Lightning NOx is found to have an ozone production efficiency of 6.5 ± 4.7 times that of surface NOx sources. This wide range of efficiencies across models is partly due to the assumed vertical distribution of the lightning source and partly to the treatment of nonmethane volatile organic compound (NMVOC) chemistry. Careful consideration of the vertical distribution of emissions is needed, given its large influence on ozone production.

Environmental drivers of Culicoides phenology: how important is species-specific variation when determining disease policy?

Since 2006, arboviruses transmitted by Culicoides biting midges (Diptera: Ceratopogonidae) have caused significant disruption to ruminant production in northern Europe. The most serious incursions involved strains of bluetongue virus (BTV), which cause bluetongue (BT) disease. To control spread of BTV, movement of susceptible livestock is restricted with economic and animal welfare impacts. The timing of BTV transmission in temperate regions is partly determined by the seasonal presence of adult Culicoides females. Legislative measures therefore allow for the relaxation of ruminant movement restrictions during winter, when nightly light-suction trap catches of Culicoides fall below a threshold (the ‘seasonally vector free period’: SVFP). We analysed five years of time-series surveillance data from light-suction trapping in the UK to investigate whether significant inter-specific and yearly variation in adult phenology exists, and whether the SVFP is predictable from environmental factors. Because female vector Culicoides are not easily morphologically separated, inter-specific comparisons in phenology were drawn from male populations. We demonstrate significant inter-specific differences in Culicoides adult phenology with the season of Culicoides scoticus approximately eight weeks shorter than Culicoides obsoletus. Species-specific differences in the length of the SVFP were related to host density and local variation in landscape habitat. When the Avaritia Culicoides females were modelled as a group (as utilised in the SFVP), we were unable to detect links between environmental drivers and phenological metrics. We conclude that the current treatment of Avaritia Culicoides as a single group inhibits understanding of environmentally-driven spatial variation in species phenology and hinders the development of models for predicting the SVFP from environmental factors. Culicoides surveillance methods should be adapted to focus on concentrated assessments of species-specific abundance during the start and end of seasonal activity in temperate regions to facilitate refinement of ruminant movement restrictions thereby reducing the impact of Culicoides-borne arboviruses.

The relative performance of AIC, AICC and BIC in the presence of unobserved heterogeneity

Summary Model selection is difficult. Even in the apparently straightforward case of choosing between standard linear regression models, there does not yet appear to be consensus in the statistical ecology literature as to the right approach. We review recent works on model selection in ecology and subsequently focus on one aspect in particular: the use of the Akaike Information Criterion (AIC) or its small-sample equivalent, AICC. We create a novel framework for simulation studies and use this to study model selection from simulated data sets with a range of properties, which differ in terms of degree of unobserved heterogeneity. We use the results of the simulation study to suggest an approach for model selection based on ideas from information criteria but requiring simulation. We find that the relative predictive performance of model selection by different information criteria is heavily dependent on the degree of unobserved heterogeneity between data sets. When heterogeneity is small, AIC or AICC are likely to perform well, but if heterogeneity is large, the Bayesian Information Criterion (BIC) will often perform better, due to the stronger penalty afforded. Our conclusion is that the choice of information criterion (or more broadly, the strength of likelihood penalty) should ideally be based upon hypothesized (or estimated from previous data) properties of the population of data sets from which a given data set could have arisen. Relying on a single form of information criterion is unlikely to be universally successful.

MINITAB MACROS FOR RESAMPLING METHODS

Summary This article describes a set of Minitab macros that perform randomization and bootstrap versions of basic statistical techniques, and suggests ways in which the macros might be used in teaching statistics.