TGI Friday! Our weekly round-up of recently published research abstracts | 11 November 2016

November 11, 2016


From Gut Microbes, 3 November 2016

Support for the Microgenderome Invites Enquiry into Sex Differences

Amy Wallis(1), Henry Butt(2), Michelle Ball(1), Donald P. Lewis(3) & Dorothy Bruck (1)
(1) Psychology Department, Victoria University, Victoria, Australia
(2) Bioscreen (Aust) Pty Ltd, Victoria, Australia
(3) CFS Discovery Clinic, Donvale, Victoria, Australia
Correspondence: amy.wallis@vu.edu.au

Abstract

The microgenderome defines the interaction between microbiota, sex hormones and the immune system. Our recent research inferred support for the microgenderome by showing sex differences in microbiota-symptom associations in a clinical sample of patients with myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS).

This addendum expands upon the sex-specific pattern of associations that were observed. Interpretations are hypothesised in relation to genera versus species-level analyses and D-lactate theory.

Evidence of sex-differences invites future research to consider sex comparisons in microbial function even when microbial abundance is statistically similar. Pairing assessment of clinical symptoms with microbial culture, DNA sequencing and metabolomics methods will help advance our current understandings of the role of the microbiome in health and disease.


From Fatigue: Biomedicine, Health & Behavior (journal of the International Association for CFS/ME), 12 October 2016.

Mortality in patients with myalgic encephalomyelitis and chronic fatigue syndrome

Stephanie L. McManimen, Andrew R. Devendorf, Abigail A. Brown, Billie C. Moore, James H. Moore & Leonard A. Jason
Center for Community Research, De Paul University, Chicago, Illinois, USA

Abstract

BACKGROUND

There is a dearth of research examining mortality in individuals with myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Some studies suggest there is an elevated risk of suicide and earlier mortality compared to national norms. However, findings are inconsistent.

OBJECTIVE

This study sought to determine if patients are reportedly dying earlier than the overall population from the same cause.

METHODS

Family, friends, and caregivers of deceased patients were recruited. This study analyzed data including cause and age of death for 56 individuals.

RESULTS

The findings suggest patients in this sample are at a significantly increased risk of earlier all-cause (M = 55.9 years) and cardiovascular-related (M = 58.8 years) mortality, and they had a directionally lower age of death for suicide (M = 41.3 years) and cancer (M = 66.3 years) compared to the overall U.S. population [M = 73.5 (all-cause), 77.7 (cardiovascular), 47.4 (suicide), and 71.1 (cancer) years of age].

CONCLUSIONS

Results suggest there is an increase in risk for earlier mortality in patients. Due to sample size and over-representation of severely ill patients, the findings should be replicated to determine if the directional differences for suicide and cancer mortality are significantly different from the overall population.


From PLoS One, 2 November 2016

Metagenomic Investigation of Plasma in Individuals with ME/CFS Highlights the Importance of Technical Controls to Elucidate Contamination and Batch Effects

Ruth R. Miller
Affiliation School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
Miguel Uyaguari-Diaz
Affiliation British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
Mark N. McCabe
Affiliation British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
Vincent Montoya
Affiliation British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
Jennifer L. Gardy
Affiliations School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
Shoshana Parker
Affiliation Centre for Health Evaluation and Outcome Sciences, Vancouver, British Columbia, Canada
Theodore Steiner
Affiliation Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
William Hsiao
Affiliations British Columbia Public Health Microbiology and Reference Laboratory, Vancouver, British Columbia, Canada, Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
Matthew J. Nesbitt
Affiliation Coastal Genomics Inc., Burnaby, British Columbia, Canada
Patrick Tang
Affiliation Department of Pathology, Sidra Medical and Research Center, Doha, Qatar
David M. Patrick
* E-mail: david.patrick@ubc.ca
Affiliations School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
for the CCD Study Group
Membership of the CCD Study Group is provided in the Acknowledgments.

Abstract

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease causing indefinite fatigue. ME/CFS has long been hypothesised to have an infectious cause; however, no specific infectious agent has been identified.

We used metagenomics to analyse the RNA from plasma samples from 25 individuals with ME/CFS and compare their microbial content to technical controls as well as three control groups: individuals with alternatively diagnosed chronic Lyme syndrome (N = 13), systemic lupus erythematosus (N = 11), and healthy controls (N = 25).

We found that the majority of sequencing reads were removed during host subtraction, thus there was very low microbial RNA content in the plasma. The effects of sample batching and contamination during sample processing proved to outweigh the effects of study group on microbial RNA content, as the few differences in bacterial or viral RNA abundance we did observe between study groups were most likely caused by contamination and batch effects.

Our results highlight the importance of including negative controls in all metagenomic analyses, since there was considerable overlap between bacterial content identified in study samples and control samples. For example, Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodes were found in both study samples and plasma-free negative controls.

Many of the taxonomic groups we saw in our plasma-free negative control samples have previously been associated with diseases, including ME/CFS, demonstrating how incorrect conclusions may arise if controls are not used and batch effects not accounted for.


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