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Volume 5, Issue 3 (Suppl)

J Infect Dis Ther, an open access journal

ISSN:2332-0877

Infectious Diseases 2017

August 21-23, 2017

Annual Congress on

Infectious Diseases

August 21-23, 2017 San Francisco, USA

Microbiota in relation to obesity among healthy Saudi females

Steve Harakeh, Suhad Bahijri, Ghada Ajabnoor, Ahmed Al-Hejin, Suha Farraj, Salah Birnawi

and

Esam Azhar

King Fahd Medical Research Center, Saudi Arabia

Background:

Obesity has been considered as one of themajor modern global epidemics and a risk factor for both cardiovascular

diseases (CVD) and diabetes. There is a rapid rise in the rate of overweight and obese people in the Kingdom of Saudi Arabia

which has a tremendous impact on health and economic resources. Gut microbiota has lately been a major factor for many

metabolic disorders and diseases, including obesity, diabetes, and CVD.

Objective:

The aim of this research was to define those specific gut microbiota that are obesity-associated as determined based

on mass index (BMI) among healthy Saudi females.

Methodology:

120 healthy females, below the age of 30, with different degrees of obesity were included in this study. All the

participants had to fill out a questionnaire concerning their nutritional habits, health conditions and demographics. Their

height, body weight, hip and waist circumference were measured and their BMI was determined accordingly. Stool samples

were collected and genomic DNAwas extracted from our study group. The DNA samples were sequenced using next generation

sequencing (MiSeq), sequencing reads were trimmed, analyzed and filtered and assigned to taxonomic units.

Results:

The results revealed the existence of different bacteriological groups including

Firmicutes

Actinomyces odontolyticus

Escherichia coli

and

Ruminococcus obeum

and others. Work is in progress to correlate the prevalence of those bacterial groups

with BMI.

Conclusion & Recommendations:

The data showed the presence of a variety of bacterial strains and microbiota populations

among our study individuals. Bioinformatics data analysis will help to identify certain microbiota marker populations to be

associated with different stages of obesity among the female Saudi population. Final goal is an early prediction of obesity and

to target those patient groups to treat obesity.

Steve Harakeh et al., J Infect Dis Ther 2017, 5:3 (Suppl)

DOI: 10.4172/2332-0877-C1-026