scholarly journals A statistical dynamics approach to the study of human health data: Resolving population scale diurnal variation in laboratory data

2010 ◽  
Vol 374 (9) ◽  
pp. 1159-1164 ◽  
Author(s):  
D.J. Albers ◽  
George Hripcsak
2018 ◽  
Vol 12 ◽  
pp. 117863021775190 ◽  
Author(s):  
Brittany Corley ◽  
Shannon Bartelt-Hunt ◽  
Eleanor Rogan ◽  
Donald Coulter ◽  
John Sparks ◽  
...  

In 2009, a paper was published suggesting that watersheds provide a geospatial platform for establishing linkages between aquatic contaminants, the health of the environment, and human health. This article is a follow-up to that original article. From an environmental perspective, watersheds segregate landscapes into geospatial units that may be relevant to human health outcomes. From an epidemiologic perspective, the watershed concept places anthropogenic health data into a geospatial framework that has environmental relevance. Research discussed in this article includes information gathered from the literature, as well as recent data collected and analyzed by this research group. It is our contention that the use of watersheds to stratify geospatial information may be both environmentally and epidemiologically valuable.


2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Andrew Hatch ◽  
James Horne ◽  
Ryan Toma ◽  
Brittany L. Twibell ◽  
Kalie M. Somerville ◽  
...  

A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiome’s functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intrasample variability, rapid changes, and RNA degradation. Here, we describe a robust and automated stool metatranscriptomic method, called Viomega, which was specifically developed for population-scale studies. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. We applied this method to 10,000 human stool samples and performed several small-scale studies to demonstrate sample stability and consistency. In summary, Viomega is an inexpensive, high-throughput, automated, and accurate sample-to-result stool metatranscriptomic technology platform for large-scale studies and a wide range of applications.


2011 ◽  
Vol 11 (1) ◽  
pp. 9-14 ◽  
Author(s):  
Sarah K. Rhea ◽  
Seth W. Glickman ◽  
Anna Waller ◽  
Amy Ising ◽  
Jean-Marie Maillard ◽  
...  

2011 ◽  
Vol 30 (5) ◽  
pp. 470-479 ◽  
Author(s):  
Howard S. Burkom ◽  
Liane Ramac-Thomas ◽  
Steven Babin ◽  
Rekha Holtry ◽  
Zaruhi Mnatsakanyan ◽  
...  

Author(s):  
Habib Shah ◽  
Rozaida Ghazali ◽  
Tutut Herawan ◽  
Sami Ur Rahman ◽  
Nawsher Khan

2019 ◽  
Author(s):  
Andrew Hatch ◽  
James Horne ◽  
Ryan Toma ◽  
Brittany L. Twibell ◽  
Kalie M. Somerville ◽  
...  

The gut microbiome plays a major role in many chronic diseases. It is the only “organ” in our body whose function can easily be manipulated by our diet and lifestyle. Using personalized nutrition should enable precise control of the gut microbiome’s functions that support human health and prevent chronic diseases. Without a functional readout of the gut microbiome, however, personalized nutrition cannot be realized.Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome. Despite its usefulness, metatranscriptomics has seen very limited use in clinical studies due to its complexity, cost, and bioinformatic challenges associated with both microbial taxonomy and functions. This method has also received some criticism due to potential intra-sample variability, rapid changes, and RNA degradation.Here, we describe a robust and automated stool metatranscriptomic method, Viomega. This method was specifically developed for population-scale studies on the effects of gut microbiome on human health and disease, with the goal to develop personalized nutrition algorithms. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes.In this report, we demonstrate the robustness of Viomega technology. We also applied the method to 10,000 human stool samples and report the taxonomic and functional data. Finally, we performed several small clinical studies to demonstrate the connections between diet and the gut metatranscriptome.


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