Transcription factors direct epigenetic reprogramming at specific loci in human cancers

The characterization of epigenetic changes during cancer development and progression led to notable insights regarding the roles of cancer-specific epigenetic reprogramming. Recent studies showed that transcription factors (TFs) are capable to regulate epigenetic reprogramming at specific loci in different cancer types through their DNA-binding activities. However, the causal association of dynamic histone modification change mediated by TFs is still not well elucidated. Here we evaluated the impacts of 636 transcription factor binding activities on histone modification in 24 cancer types. We performed Instrumental Variables analysis by using genetic lesions of TFs as our instrumental proxies, which previously discovered to be associated with histone mark activities. As a result, we showed a total of 6 EpiTFs as strong directors of epigenetic reprogramming of histone modification in cancers, which alters the molecular and clinical phenotypes of cancer. Together our findings highlight a causal mechanism driven by the TFs and genome-wide histone modification, which is relevant to multiple status of oncogenesis.

The value of health-Empirical issues when estimating the monetary value of a quality-adjusted life year based on well-being data

Decisions on interventions or policy alternatives affecting health can be informed by economic evaluations, like cost-benefit or cost-utility analyses. In this context, there is a need for valid estimates of the monetary equivalent value of health (gains), which are often expressed in € per quality-adjusted life years (QALYs). Obtaining such estimates remains methodologically challenging, with a recent addition to the health economists' toolbox, which is based on well-being data: The well-being valuation approach. Using general population panel data from Germany, we put this approach to the test by investigating several empirical and conceptual challenges, such as the appropriate functional specification of income utility, the choice of health utility tariffs, or the health state dependence of consumption utility. Depending on specification, the bulk of estimated € per QALY values ranged from €20,000-60,000, with certain specifications leading to more considerable deviations, underlining persistent practical challenges when applying the well-being valuation methodology to health and QALYs. Based on our findings, we formulate recommendations for future research and applications.

Impact of Poultry Farmers' Participation in Modern Food Retail Markets on Household Dietary Diversity: Lessons from Southeast Nigeria

Simple Summary

Developing countries’ food systems are experiencing rapid transformations led by modern food retail market (MFRM) channels such as supermarkets, fast food firms, hotels, and convenience stores. This paper analyzes the impact of these channels on farm households’ dietary diversity with survey data from Southeast Nigeria. Estimates from the instrumental variable model show that participation in MFRM is associated with a significant increase in dietary diversity. Furthermore, the linkages through which MFRM participation impacts dietary diversity are analyzed using seemingly unrelated regression. Poultry farm income, consumption of poultry products produced by the farmer, and area of vegetable cultivated using poultry droppings have positive association with dietary diversity, while male controlled poultry farm revenue has negative association with dietary quality. Our study provides useful insights that poultry farm managers would find helpful. It also serves as a potential source of information for policymakers for planning as it links smallholder poultry farmers’ participation in modern food retail markets to improved nutrition.

Abstract

This study analyzed the interrelationships between participation in MFRMs and dietary diversity of poultry farming households in Southeast Nigeria. We used cross-sectional data from poultry farmers in Southeast Nigeria and employed instrumental variable and seemingly unrelated regression models to estimate the impact of MFRM participation and major linkages to poultry farm households’ dietary diversity. The results show that participating in MFRMs, relative to traditional markets, improved poultry farmers’ dietary diversity. Moreover, dietary diversity was positively related to higher poultry farm incomes, higher value of own poultry products consumed, and larger area of vegetable cultivated using poultry droppings as manure. Furthermore, increased poultry farm income, higher value of own poultry products consumed, and larger area of vegetable land cultivated using poultry droppings as manure increased the dietary diversity of the farm households. In contrast, a higher share of poultry production revenue controlled by men reduced household dietary diversity. These findings make clear the potential of improving farming households’ nutrition outcomes by promoting participation in MFRMs and the major impact pathways.

Integrative analysis of genetical genomics data incorporating network structures

In a living organism, tens of thousands of genes are expressed and interact with each other to achieve necessary cellular functions. Gene regulatory networks contain information on regulatory mechanisms and the functions of gene expressions. Thus, incorporating network structures, discerned either through biological experiments or statistical estimations, could potentially increase the selection and estimation accuracy of genes associated with a phenotype of interest. Here, we considered a gene selection problem using gene expression data and the graphical structures found in gene networks. Because gene expression measurements are intermediate phenotypes between a trait and its associated genes, we adopted an instrumental variable regression approach. We treated genetic variants as instrumental variables to address the endogeneity issue. We proposed a two-step estimation procedure. In the first step, we applied the LASSO algorithm to estimate the effects of genetic variants on gene expression measurements. In the second step, the projected expression measurements obtained from the first step were treated as input variables. A graph-constrained regularization method was adopted to improve the efficiency of gene selection and estimation. We theoretically showed the selection consistency of the estimation method and derived the L ∞ bound of the estimates. Simulation and real data analyses were conducted to demonstrate the effectiveness of our method and to compare it with its counterparts.