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Moving Toward Precision: Understandi...

Hung, Kin Wai Tony.

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Moving Toward Precision: Understanding the Heterogeneity of Obesity.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Moving Toward Precision: Understanding the Heterogeneity of Obesity./
作者:	Hung, Kin Wai Tony.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	48 p.
附註:	Source: Masters Abstracts International, Volume: 82-01.
Contained By:	Masters Abstracts International82-01.
標題:	Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28001184
ISBN:	9798641071657

Moving Toward Precision: Understanding the Heterogeneity of Obesity.
Hung, Kin Wai Tony.

Moving Toward Precision: Understanding the Heterogeneity of Obesity. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 48 p.

Source: Masters Abstracts International, Volume: 82-01.

Thesis (M.S.)--University of California, Los Angeles, 2020.

This item must not be sold to any third party vendors.

Background: Obesity is a global health pandemic that has been linked to detrimental health and socioeconomic impact. Growing evidence have recognized obesity as a spectrum of metabolic imbalances with complex biopsychosocial interactions including the brain-gut axis. A precision understanding on obesity while at its infancy is necessary to accelerate reduction of its health burden. Methods: With our aim to better understand the biopsychosocial interactions at the transitional junction of obesity development, we conducted a cross sectional study in overweight and obese individuals. Univariate and multivariate logistic regression models were used to examine obesity and its association with sociodemographic, clinical, and dietary-behavioral factors. Biological interactions including the gut microbiome, gut amino acids and brain structural volumes were also examined. Microbial data were analyzed for alpha diversity, beta diversity, and relative abundance of taxa. Amino acids and brain structural volumes were analyzed using multiple ANOVA. Interactions were tested by Pearson correlations and corrected for multiple hypothesis. Results: Among 130 participants, there were higher odds of obesity if individuals were Hispanic [Adjusted Odds Ratio (AOR) 1.70, p = 0.0089], and married (AOR 1.63, p = 0.036). Compared to non-Hispanic, Hispanic had a significantly different microbiome profile (p = 0.046) with lower microbial species richness (Chao1) (p = 0.032) and evenness (Shannon) (p = 0.0029). A predominance of the phylum Firmicutes was positively correlated to American diet consumption (p = 0.036) while negatively correlated to Hispanic ethnicity (p = 0.021). Fourteen of twenty gut amino acids including all essential amino acids were increased among Hispanics (p < 0.05). Brain structural volumes in reward regions were decreased especially if individuals were Hispanic (pallidum, p = 0.036; brainstem, p = 0.011), married (left thalamus, p = 0.024), or consumed an American diet (brainstem, p = 0.043). Conclusions: Hispanic expressed a unique gut microbial signature, which was associated with obesity despite sociodemographic, clinical, and dietary differences. Gut amino acids and brain structural volumes may further differentiate Hispanic ethnic differences and warrant future research. Addressing ethnic disparities guided by biologic phenotypes may unlock novel understanding of obesity heterogeneity and transform its impact on obesity care.

ISBN: 9798641071657Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Brain gut axis

Moving Toward Precision: Understanding the Heterogeneity of Obesity.
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