Comparing methods for modeling longitudinal and survival data, with consideration of mediation analysis

Joint modeling of longitudinal and survival data has received much attention and is becoming increasingly useful. In clinical studies, longitudinal biomarkers are used to monitor disease progression and to predict survival. These longitudinal measures are often missing at failure times and may be prone to measurement errors. In previous studies these two types of data are frequently analyzed separately where a mixed effects model is used for longitudinal data and a survival model is applied to event outcomes. The argument in favor of a joint model has been the efficient use of the data as the survival information goes into modeling the longitudinal process and vice versa. In this thesis, we present joint maximum likelihood methods, a two stage approach and time dependent covariate methods that link longitudinal data to survival data. First, we use simulation studies to explore and assess the performance of these methods with bias, accuracy and coverage probabilities. Then, we focus on four time dependent methods considering models that are unadjusted and adjusted for time. Finally, we consider mediation analysis for longitudinal and survival data. Mediation analysis is introduced and applied in a research framework based on genetic variants, longitudinal measures and disease risk. We implement accelerated failure time regression using the joint maximum likelihood approach (AFT-joint) and an accelerated failure time regression model using the observed longitudinal measures as time dependent covariates (AFT-observed) to assess the mediated effect. We found that the two stage approach (TSA) performed best at estimating the link parameter. The joint maximum likelihood methods that used the predicted values of the longitudinal measures, similar to the TSA, provided larger estimates. The time dependent covariate methods that used the observed longitudinal measures in the survival analysis underestimated the true estimates. The mediation results showed that the AFT-joint and the AFT-observed underestimated the mediated effect. Comparison of the methods in Framingham Heart Study data revealed similar patterns. We recommend adjusting for time when estimating the association parameter in time dependent Cox and logistic models. Additional work is needed for estimating the mediated effect with longitudinal and survival data

Regression Models for Mixed Over-Dispersed Poisson and Continuous Clustered Data: Modeling BMI and Number of Cigarettes Smoked Per Day

Clustered data, multiple observations collected on the same experimental unit, is common in epidemiological studies. Bivariate outcome data is often the result of interest in two correlated response variables. An efficient method is presented for dealing with bivariate outcomes when one outcome is continuous and the other is a count using a simple transformation to handle over-dispersed Poisson data. A multilevel analysis was performed on data from the National Health Interview Survey (NHIS) with body mass index (BMI) and the number of cigarettes smoked per day (NCS) as responses. Results show that these random effects models yield misleading results in cases where the data is not transformed

The Biology of Malaria Gametocytes

Gametocytes are sexual precursor cells of the malaria parasite that mediate the transmission of the parasite from its mammalian host to the Anopheles mosquito. Unlike the asexual blood stages, which are responsible for the clinical outcome of malaria, gametocytes cause no clinical manifestations. However, they are very crucial for the transmission of the disease thus represent key targets for transmission-blocking interventions. Despite their essential role in malaria transmission, only in the last decade gametocytes became a hot topic of research and their biology is not well understood. This chapter provides a detailed review on the biology of the human malaria gametocytes with emphasis on aspects such as gametocyte commitment, gametocyte maturation (gametocytogenesis), gametocyte metabolism and gametogenesis. Proper understanding of these processes will deepen our knowledge on the gametocyte biology and therefore open up more avenues for the development of malaria transmission-blocking intervention strategies

Designing an Educational Program to Promote Diversity and Student Engagement in Professional Advocacy (SEPA)

Little is understood about best educational strategies to engage diverse occupational therapy students in professional advocacy. The purpose of this research was to use design-based research (DBR) methods to design a novel educational intervention to promote professional engagement of diverse students over three subsequent years. This study used a pre/post design to design, implement, evaluate, and revise an educational program entitled “Student Engagement in Professional Advocacy” (SEPA). This manuscript reports on the first year of that study. The participants (N=27) were entry-level Master of Science occupational therapy students. The outcome measure was a survey measuring student knowledge, attitude, and participation specific to professional advocacy. All participants completed the pre and post surveys and participated in four SEPA educational modules. Significant differences were observed in pre and post scores in knowledge (p \u3c 0.0001), action (p= 0.004), and attitude (p=0.012). This suggests that SEPA was effective at increasing student knowledge of, attitudes toward, and participation in professional advocacy. Pearson correlation of domains revealed a strong positive association between knowledge and attitude (p= 0.0003), actions and attitude (p = 0.0018), and action and knowledge (p=0.0262). This indicates that educational programs promoting professional engagement should address knowledge and attitudes and provide opportunities for participation. Qualitative data provided additional information on how students integrated professional engagement into their identity as students, and practical feedback on how to improve the program. Study findings supported the use of SEPA to promote student professional engagement. Further research is indicated, including conducting additional iterations of the project to continue to refine SEPA

Pathway analysis following association study

Genome-wide association studies often emphasize single-nucleotide polymorphisms with the smallest p-values with less attention given to single-nucleotide polymorphisms not ranked near the top. We suggest that gene pathways contain valuable information that can enable identification of additional associations. We used gene set information to identify disease-related pathways using three methods: gene set enrichment analysis (GSEA), empirical enrichment p-values, and Ingenuity pathway analysis (IPA). Association tests were performed for common single-nucleotide polymorphisms and aggregated rare variants with traits Q1 and Q4. These pathway methods were evaluated by type I error, power, and the ranking of the VEGF pathway, the gene set used in the simulation model. GSEA and IPA had high power for detecting the VEGF pathway for trait Q1 (91.2% and 93%, respectively). These two methods were conservative with deflated type I errors (0.0083 and 0.0072, respectively). The VEGF pathway ranked 1 or 2 in 123 of 200 replicates using IPA and ranked among the top 5 in 114 of 200 replicates for GSEA. The empirical enrichment method had lower power and higher type I error. Thus pathway analysis approaches may be useful in identifying biological pathways that influence disease outcomes

The human parasite Loa loa in cytokine and cytokine receptor gene knock out BALB/c mice: survival, development and localization

<p>Abstract</p> <p>Background</p> <p>Immunological mechanisms involved in the survival and development of human filarial species in the vertebrate host are poorly known due to the lack of suitable experimental models. In order to understand the role of cytokines in the survival and development of filarial larvae in the vertebrate host, we infected different strains of BALB/c mice deficient in a number of cytokine or cytokine receptor genes with <it>Loa loa</it>. The survival and development of larvae were monitored.</p> <p>Methods</p> <p>BALB/c mice genetically deficient in IL-4R, IFN-γ, IFN-γ/IL-5, IL-5, and IL-4R/IL-5 cytokine or cytokine receptor genes were infected with a human strain of <it>L. loa </it>and necropsies were performed at different time intervals up to 70 days post infection to monitor the survival and development of <it>L. loa </it>larvae. The larvae were teased out of the skin, muscles, peritoneal and pleural cavities, heart and lung tissues. The length and width of the recovered larvae were measured to assess their growth.</p> <p>Results</p> <p>In mice deficient for IL-4R, IFN-γ, IFN-γ/IL-5, IL-5 and IL-4R/IL-5, the larvae survived up to 5, 20, 40, 50 and 70 days respectively. Worms recovered 70 days post infection in IL-4R/IL-5 DKO mice were young adults and measured 10.12 mm in length and 0.1 mm in width. Overall, 47% of larvae were recovered from subcutaneous tissues, 40% from muscles, 6% from the peritoneal cavity and 4% from the pleural cavity, lungs and heart.</p> <p>Conclusion</p> <p><it>L. loa </it>exhibits a differential survival and development in different strains of cytokine or cytokine receptor gene knockout mice with IL-4R and IL-5 playing critical roles in the host resistance to <it>L. loa </it>infection. The knock out BALB/c mouse therefore represents a useful tool to explore the key effectors of adaptive immunity involved in the killing of the <it>L. loa </it>parasite in a mammal host.</p

Incorporating biological knowledge in the search for gene × gene interaction in genome-wide association studies

We sought to find significant gene × gene interaction in a genome-wide association analysis of rheumatoid arthritis (RA) by performing pair-wise tests of interaction among collections of single-nucleotide polymorphisms (SNPs) obtained by one of two methods. The first method involved screening the results of the genome-wide association analysis for main effects p-values < 1 × 10-4. The second method used biological databases such as the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes to define gene collections that each contained one of four genes with known associations with RA: PTPN22, STAT4, TRAF1, and C5. We used a permutation approach to determine whether any of these SNP sets had empirical enrichment of significant interaction effects. We found that the SNP set obtained by the first method was significantly enriched with significant interaction effects (empirical p = 0.003). Additionally, we found that the "protein complex assembly" collection of genes from the Gene Ontology collection containing the TRAF1 gene was significantly enriched with interaction effects with p-values < 1 × 10-8 (empirical p = 0.012)

Harmonine, a defence compound from the harlequin ladybird, inhibits mycobacterial growth and demonstrates multi-stage antimalarial activity

The harlequin ladybird beetle Harmonia axyridis has been introduced in many countries as a biological control agent, but has become an invasive species threatening the biodiversity of native ladybirds. Its invasive success has been attributed to its vigorous resistance against diverse pathogens. This study demonstrates that harmonine ((17R,9Z)-1,17-diaminooctadec-9-ene), which is present in H. axyridis haemolymph, displays broad-spectrum antimicrobial activity that includes human pathogens. Antibacterial activity is most pronounced against fast-growing mycobacteria and Mycobacterium tuberculosis, and the growth of both chloroquine-sensitive and -resistant Plasmodium falciparum strains is inhibited. Harmonine displays gametocytocidal activity, and inhibits the exflagellation of microgametocytes and zygote formation. In an Anopheles stephensi mosquito feeding model, harmonine displays transmission-blocking activity

Genetic correlations of psychiatric traits with body composition and glycemic traits are sex- and age-dependent

Peer reviewedPublisher PD

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.