Association of lipopolysaccharide-binding protein with increases in liver fat in African ancestry men

Non-alcoholic fatty liver disease (NAFLD) is a disease with increasing prevalence worldwide, especially in developed countries. While the etiology of NAFLD is complex, the intestinal microbiome may play a role in the development of liver steatosis through bacterial-induced inflammation. Lipopolysaccharide-binding protein (LBP) is an acute-phase protein produced by the liver and which facilitates bacterial-induced inflammation. LBP levels in the serum tend to be low but are raised during infection or in the presence of bacterial components; thus, levels of LBP are considered to be reflective of bacterial-induced inflammation. While the association of LBP with NAFLD has been investigated in cross-sectional studies, no longitudinal studies have been done to determine if LBP levels are associated with liver fat accumulation. Furthermore, no studies have been performed which show the heritability of LBP levels, which may affect susceptibility to the inflammatory response. Elucidation of the role of LBP in NAFLD can provide insights into the etiology of NAFLD and provide a mechanistic link between the intestinal microbiome and liver fat accumulation, yielding public health importance for the understanding and treatment of NAFLD. This study is the first longitudinal study to look at the associations of LBP with the development of steatosis and it is the first study to determine the heritability of LBP in any population, thus supplying novel information on the associations between LBP and liver fat accumulation. A large family-based study of African ancestry men and women (N = 470) and a large prospective cohort study of African ancestry men (N = 2853) from Tobago were used for this study. LBP was measured in all individuals in the family study. Heritability analyses were performed using SOLAR. In the prospective cohort study, LBP levels were measured at baseline visit (2004-2007), and liver fat was assessed at the follow-up visit (2013-2016, ~10 years later) by computerized tomography (CT) scan, with an overlap of 204 men having both LBP and liver CT completed. Associations were assessed using Spearman correlations and regression analyses. LBP levels in the families were found to have no residual heritability, suggesting that LBP might be entirely environmentally determined in this population. In the prospective cohort, LBP was associated with liver fat infiltration in multivariable analyses which included BMI (p = 0.0469), but not in models which instead included waist circumference. In conclusion, we determined that among African ancestry individuals, LBP levels are completely environmentally determined and that levels may be associated with increases in liver fat accumulation

The Euclid Statistical Matrix Tool

Stataphobia, a term used to describe the fear of statistics and research methods, can result from a lack of improper training in statistical methods. Poor statistical methods training can have an effect on health policy decision making and may play a role in the low research productivity seen in developing countries. One way to reduce Stataphobia is to intervene in the teaching of statistics in the classroom; however, such an intervention must tackle several obstacles, including student interest in the material, multiple ways of learning materials, and language barriers.We present here the Euclid Statistical Matrix, a tool for combatting Stataphobia on a global scale. This free tool is comprised of popular statistical YouTube channels and web sources that teach and demonstrate statistical concepts in a variety of presentation methods. Working with international teams in Iran, Japan, Egypt, Russia, and the United States, we have also developed the Statistical Matrix in multiple languages to address language barriers to learning statistics. By utilizing already-established large networks, we are able to disseminate our tool to thousands of Farsi-speaking university faculty and students in Iran and the United States. Future dissemination of the Euclid Statistical Matrix throughout the Central Asia and support from local universities may help to combat low research productivity in this region

The Impacts of Adipose Tissue and the Gut Microbiome on Diabetes Risk among African-Caribbean Men

Type 2 diabetes (T2D) and its complications are increasing in prevalence and burden worldwide. Caribbean rates of T2D rival those of the United States, and mortality from T2D is exceptionally higher. The study of novel T2D risk factors, such as adipose tissue (AT) radiodensity, AT distribution, and the intestinal microbiome, yield greater insights into T2D pathophysiology and can inform targeted interventions. However, individuals of African ancestry, who have a higher burden of T2D compared to Caucasian counterparts, are underrepresented in this research. Thus, this dissertation fills the gaps by investigating associations of AT radiodensity, body composition, and the intestinal microbiome with T2D in a cohort of African Caribbean men from Tobago, Trinidad and Tobago. The first dissertation paper investigates associations between AT radiodensity in the abdomen (visceral [VAT] and subcutaneous [SAT]) and thigh (intermuscular [IMAT]) with glucose, insulin, and insulin resistance. We demonstrate that lower radiodensity in any AT (indicating greater tissue lipid accumulation) was associated with higher insulin and insulin resistance, with independent contributions from thigh IMAT. The second dissertation paper models the associations of both AT and muscle from the abdomen and thigh with T2D. We report that abdominal SAT (but not VAT) was positively associated, and thigh muscle negatively associated, with higher odds of T2D. The third dissertation paper examines associations of the intestinal microbiome with sociodemographic, lifestyle, body composition, and T2D measures. We identified sociodemographic factors as a main driver of microbial clustering, and several lifestyle and body composition measures as being differentially associated with taxonomic units, thus informing future prediction modeling of the microbiome with T2D. These findings have significant public health implications. Our results somewhat differ from those reported in predominantly Caucasian cohorts, highlighting the importance of including racial/ethnic minorities in novel risk factor research. These papers also provide important methodological work, informing how body composition analyses are performed. Finally, this research produced the first nutritional and microbiome databases in Tobago, which can aid future T2D research. Taken together, information from this dissertation can be leveraged to inform future observational and interventional studies in T2D prevention, both in the Caribbean and worldwide

The Euclid Statistical Matrix Tool

Stataphobia, a term used to describe the fear of statistics and research methods, can result from a lack of improper training in statistical methods. Poor statistical methods training can have an effect on health policy decision making and may play a role in the low research productivity seen in developing countries. One way to reduce Stataphobia is to intervene in the teaching of statistics in the classroom; however, such an intervention must tackle several obstacles, including student interest in the material, multiple ways of learning materials, and language barriers. We present here the Euclid Statistical Matrix, a tool for combatting Stataphobia on a global scale. This free tool is comprised of popular statistical YouTube channels and web sources that teach and demonstrate statistical concepts in a variety of presentation methods. Working with international teams in Iran, Japan, Egypt, Russia, and the United States, we have also developed the Statistical Matrix in multiple languages to address language barriers to learning statistics. By utilizing already-established large networks, we are able to disseminate our tool to thousands of Farsi-speaking university faculty and students in Iran and the United States. Future dissemination of the Euclid Statistical Matrix throughout the Central Asia and support from local universities may help to combat low research productivity in this region