Reporting and evaluating genetic association studies

Transcription factor HIF1A: downstream targets, associated pathways, polymorphic hypoxia response element (HRE) sites, and initiative for standardization of reporting in scientific literature

Hypoxia-inducible factor-1α (HIF-1α) has crucial role in adapting cells to hypoxia through expression regulation of many genes. Identification of HIF-1α target genes (HIF-1α-TGs) is important for understanding the adapting mechanism. The aim of the present study was to collect known HIF-1α-TGs and identify their associated pathways. Targets and associated genomics data were retrieved using PubMed, WoS ( http://apps.webofknowledge.com/ ), HGNC ( http://www.genenames.org/ ), NCBI ( http://www.ncbi.nlm.nih.gov/ ), Ensemblv.84 ( http://www.ensembl.org/index.html ), DAVID Bioinformatics Resources ( https://david.ncifcrf.gov /), and Disease Ontology database ( http://disease-ontology.org/ ). From 51 papers, we collected 98 HIF-1α TGs found to be associated with 20 pathways, including metabolism of carbohydrates and pathways in cancer. Reanalysis of genomic coordinates of published HREs (hypoxia response elements) revealed six polymorphisms within HRE sites (HRE-SNPs): ABCG2, ACE, CA9, and CP. Due to large heterogeneity of results presentation in scientific literature, we also propose a first step towards reporting standardization of HIF-1α-target interactions consisting of ten relevant data types. Suggested minimal checklist for reporting will enable faster development of a complete catalog of HIF-1α-TGs, data sharing, bioinformatics analyses, and setting novel more targeted hypotheses. The proposed format for data standardization is not yet complete but presents a baseline for further optimization of the protocol with additional details, for example, regarding the experimental validation.

Future Perspectives of Personalized Weight Loss Interventions Based on Nutrigenetic, Epigenetic, and Metagenomic Data

As obesity has become a major global public health challenge, a large number of studies have analyzed different strategies aimed at inducing a negative energy balance and, consequently, body weight loss. However, most existing weight loss programs are generally unsuccessful, so several interventions have been carried out to identify physiologic and behavioral factors concerning this variability in order to implement more personalized treatment. Nowadays, an individualized approach is being proposed through so-called personalized nutrition, whereby not only the phenotype but also the genotype is used for customized nutrition treatment. Regarding body weight regulation, ∼70 polymorphisms have been identified in or near genes related to energy expenditure, appetite, adipogenesis, insulin resistance, and lipid metabolism. Although personalized nutrition refers mainly to genetic makeup, recent advances in the investigation of the epigenome and the microbiome open the door to implement more personalized recommendations for body weight management. In this context, recent studies have demonstrated the existence of several epigenetic markers that may modify gene expression and could be involved in the outcome of weight loss interventions. Moreover, different studies have shown that dietary interventions could affect the composition of gut microbiota and have an impact on body weight. The integration of nutrigenetic, epigenetic, and metagenomic data may lead to the design of more personalized dietary treatments to prevent chronic diseases and to optimize the individual's response to dietary interventions.

Tamoxifen-induced venothromboembolic events: exploring validation of putative genetic association

OBJECTIVE

A pilot study to examine accrual rates, efficiency of data capture approaches, study design and genotyping capacity for a future genetic validation study was undertaken.

DESIGN

The process pilot evaluated feasibility of applying a matched case-control design to validate association of two candidate estrogen receptor (ER) single nucleotide polymorphisms (SNPs) with incidence of venothromboembolic events (VTE) in breast cancer patients treated with tamoxifen where criteria included frequency matching by age, number of years diagnosed with breast cancer within 4-year intervals, and geographic residency.

SETTING

The study was conducted at Marshfield Clinic, in central Wisconsin.

PARTICIPANTS

Study-eligible cases with a breast cancer diagnosis between 1994 and 2006 who experienced a VTE within 5 years of last tamoxifen exposure were matched at a ratio of 1:4 to controls with a breast cancer diagnosed between 1994 and 2006 with no VTE history following tamoxifen exposure for ≥2 years.

METHODS

Feasibility of enrolling, phenotyping, and genotyping 20% of the total number of validated eligible cases and controls was tested in order to project enrollment rates and assess probability of enrolling the projected sample size for the prospective validation study and adequacy of planned data capture. Conditional logistic regression analysis was conducted for the matched case-control study design.

RESULTS

Enrollment accruals included 19 of 24 targeted cases (79%), and 74 of 96 (77%) targeted controls. Electronic data capture for most variables was nearly 100%. No unexpected statistically significant differences were observed between cases and controls. Capacity to conduct in-house screening for rs2234689 (ER1 PvuII), rs9340799 (ER1 XbaI), rs13146272 (CYP4V2), rs2227589 (SERPINC 1) and rs1613662 (GP6) was successfully established. Association of GP6 with VTE was further validated (P=0.0403; OR, 0.19).

CONCLUSION

Accrual rates to the larger prospective study will require a multi-center design to ensure enrollment of adequate numbers of cases and controls for achieving the projected sample size required to validate association of the ER SNPs. To prevent study failure due to poor accrual, the importance of conducting feasibility studies before launching large scale validation studies of genetic association and adverse drug events, is discussed.

Proteomics in asthma and COPD phenotypes and endotypes for biomarker discovery and improved understanding of disease entities

The application of proteomics to respiratory diseases, such as asthma and COPD, has been limited compared to other fields, like cancer. Both asthma and COPD are recognised to be multi-factorial and complex diseases, both consisting of clusters of multiple disease phenotypes. The complexity of these diseases combined with the inaccessibility and invasiveness of disease relevant samples have provided a hurdle to the progress of respiratory proteomics. Advances in proteomic instrumentation and methodology have led to the possibility to identify proteomes in much smaller quantities of biological material. This review focuses on the efforts in respiratory proteomics in relation to asthma and COPD, and the importance of identifying subgroups of disease entities to establish appropriate biomarkers, and to enhance the understanding of underlying mechanisms in each subgroup. Careful phenotype characterisation of patient subpopulations is required to make improvement in the field of heterogeneous diseases such as asthma and COPD, and the clusters of phenotypes are likely to encompass subgroups of disease with distinct molecular mechanisms; endotypes. The utilisation of modern advanced proteomics in endotypes of asthma and COPD will likely contribute to the increased understanding of disease mechanisms, establishment of biomarkers for these endotypes and improved patient care.