Efficient and Robust Approaches for Analysis of SMARTs: Illustration using the ADAPT-R Trial

Personalized intervention strategies, in particular those that modify treatment based on a participant's own response, are a core component of precision medicine approaches. Sequential Multiple Assignment Randomized Trials (SMARTs) are growing in popularity and are specifically designed to facilitate the evaluation of sequential adaptive strategies, in particular those embedded within the SMART. Advances in efficient estimation approaches that are able to incorporate machine learning while retaining valid inference can allow for more precise estimates of the effectiveness of these embedded regimes. However, to the best of our knowledge, such approaches have not yet been applied as the primary analysis in SMART trials. In this paper, we present a robust and efficient approach using Targeted Maximum Likelihood Estimation (TMLE) for estimating and contrasting expected outcomes under the dynamic regimes embedded in a SMART, together with generating simultaneous confidence intervals for the resulting estimates. We contrast this method with two alternatives (G-computation and Inverse Probability Weighting estimators). The precision gains and robust inference achievable through the use of TMLE to evaluate the effects of embedded regimes are illustrated using both outcome-blind simulations and a real data analysis from the Adaptive Strategies for Preventing and Treating Lapses of Retention in HIV Care (ADAPT-R) trial (NCT02338739), a SMART with a primary aim of identifying strategies to improve retention in HIV care among people living with HIV in sub-Saharan Africa

An Approach to Nonparametric Inference on the Causal Dose Response Function

The causal dose response curve is commonly selected as the statistical parameter of interest in studies where the goal is to understand the effect of a continuous exposure on an outcome.Most of the available methodology for statistical inference on the dose-response function in the continuous exposure setting requires strong parametric assumptions on the probability distribution. Such parametric assumptions are typically untenable in practice and lead to invalid inference. It is often preferable to instead use nonparametric methods for inference, which only make mild assumptions about the data-generating mechanism. We propose a nonparametric test of the null hypothesis that the dose-response function is equal to a constant function. We argue that when the null hypothesis holds, the dose-response function has zero variance. Thus, one can test the null hypothesis by assessing whether there is sufficient evidence to claim that the variance is positive. We construct a novel estimator for the variance of the dose-response function, for which we can fully characterize the null limiting distribution and thus perform well-calibrated tests of the null hypothesis. We also present an approach for constructing simultaneous confidence bands for the dose-response function by inverting our proposed hypothesis test. We assess the validity of our proposal in a simulation study. In a data example, we study, in a population of patients who have initiated treatment for HIV, how the distance required to travel to an HIV clinic affects retention in care.Comment: 39 pages, 5 figure

Morphological Characterization and Selection of Spider Plant (Cleome Gynandra) Accessions from Kenya and South Africa

Characterization of selected spider plant accessions from Kenya and South Africa was performed in order to individuate those with distinct morphological traits for future improvement programs. For this purpose, thirty two accessions of spider plant, 23 sourced from Kenyan genebank and nine sourced from South African genebank, were planted at the University of Nairobi’s Kabete field station, in a randomized complete block design with 3 replications. Eleven morphological traits based on modified FAO (1995) spider plant descriptors were used in characterization. Traits evaluated were growth habit, flower colour, stem colour, stem hairiness, petiole colour, petiole hairiness, leaf colour, leaf pubescence, leaf shape, leaf blade tip shape, and number of leaflets per leaf. The scored data were analyzed using DARwin software v6 and Genstat v14. Shannon diversity index (H’), multivariate methods of principal component analysis and hierarchical clustering analyses of unweighted pair group method of arithmetic mean were assessed for all the traits. Estimates of Shannon-Weaver diversity index (H’) for the morphological traits were generally high (H’>0.500). The H' index indicated inter-country diversity to be greater than the intra-country diversity. Principal component analysis identified seven important morphological traits (stem colour, stem hairiness, petiole colour, petiole hairiness, leaf hairiness, leaf shape and number of leaflets per leaf) for characterizing spider plant accessions. The hierarchical cluster analysis revealed two major clusters (Cluster I and II) for the 32 accessions grown, with clustering of accessions occurring along regional basis. Cluster I consisted of South African accessions only while cluster II had mainly Kenyan accessions and two South African accessions. The relatively high levels of dissimilarity revealed in this study among the accessions for traits evaluated, especially accessions from the two different countries, indicates high prospects for genetic improvement of the crop through cross breeding by using materials from different geographical origins

Response of elite Kenyan finger millet (Eleusine coracana, L. Gaertn) genotypes to Ethrel application

Finger millet is a staple food crop of many communities in Africa. The crop is highly nutritious and has incredible grain storage quality. Limited research investment in finger millet in the past has resulted in poor yields and there are currently no commercial hybrids. We investigated the response of different finger millet genotypes (Okhale-1, Gulu-E, KACCIMMI-72, IE 2872, IE 4115 and U-15) to the application of a plant growth regulator hormone (Ethrel). Six elite Kenyan finger millet varieties with contrasting agronomic traits were crossed in a 6 x 6 diallel pattern. To enhance male sterility across female parents, we subjected the plants to Ethrel at concentrations of 1,500ppm, 1,750ppm and 2,000ppm against a 0ppm check. Dwarfing of sprayed plants that resulted in less lodging and ultimately higher yields were observed among plants sprayed with Ethrel at different concentrations. Ethrel application at 2,000ppm had the most dwarfing effect on plants while spraying plants with 1,500ppm of Ethrel resulted in increased grain weight. Although our results demonstrate overall positive effect of Ethrel on finger millet production, the optimum concentrations for more efficient hybridization will still need to be determined

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community

Defining the Transcriptome Assembly and Its Use for Genome Dynamics and Transcriptome Profiling Studies in Pigeonpea (Cajanus cajan L.)

This study reports generation of large-scale genomic resources for pigeonpea, a so-called ‘orphan crop species’ of the semi-arid tropic regions. FLX/454 sequencing carried out on a normalized cDNA pool prepared from 31 tissues produced 494 353 short transcript reads (STRs). Cluster analysis of these STRs, together with 10 817 Sanger ESTs, resulted in a pigeonpea trancriptome assembly (CcTA) comprising of 127 754 tentative unique sequences (TUSs). Functional analysis of these TUSs highlights several active pathways and processes in the sampled tissues. Comparison of the CcTA with the soybean genome showed similarity to 10 857 and 16 367 soybean gene models (depending on alignment methods). Additionally, Illumina 1G sequencing was performed on Fusarium wilt (FW)- and sterility mosaic disease (SMD)-challenged root tissues of 10 resistant and susceptible genotypes. More than 160 million sequence tags were used to identify FW- and SMD-responsive genes. Sequence analysis of CcTA and the Illumina tags identified a large new set of markers for use in genetics and breeding, including 8137 simple sequence repeats, 12 141 single-nucleotide polymorphisms and 5845 intron-spanning regions. Genomic resources developed in this study should be useful for basic and applied research, not only for pigeonpea improvement but also for other related, agronomically important legumes

Comparison of the microbial composition of African fermented foods using amplicon sequencing

Fermented foods play a major role in the diet of people in Africa, where a wide variety of raw materials are fermented. Understanding the microbial populations of these products would help in the design of specific starter cultures to produce standardized and safer foods. In this study, the bacterial diversity of African fermented foods produced from several raw materials (cereals, milk, cassava, honey, palm sap, and locust beans) under different conditions (household, small commercial producers or laboratory) in 8 African countries was analysed by 16S rRNA gene amplicon sequencing during the Workshop “Analysis of the Microbiomes of Naturally Fermented Foods Training Course”. Results show that lactobacilli were less abundant in fermentations performed under laboratory conditions compared to artisanal or commercial fermentations. Excluding the samples produced under laboratory conditions, lactobacilli is one of the dominant groups in all the remaining samples. Genera within the order Lactobacillales dominated dairy, cereal and cassava fermentations. Genera within the order Lactobacillales, and genera Zymomonas and Bacillus were predominant in alcoholic beverages, whereas Bacillus and Lactobacillus were the dominant genera in the locust bean sample. The genus Zymomonas was reported for the first time in dairy, cereal, cassava and locust bean fermentations