Men and women show different incidence and patterns of obesity, which is a major risk factor for diabetes, cardiovascular disease, and other metabolic and reproductive diseases. This project aims to understand the biological origins of these sex differences. We will use the novel mouse model, the """"""""four core genotypes"""""""" (FCG), which includes mice with testes that have XX or XY sex chromosomes, and mice with ovaries that also have either XX or XY sex chromosomes. Thus, the FCG model offers significant advantages for discriminating among several classes of biological factors that lead to sex differences, including organizational and activational effects of gonadal hormones, and direct effects of X and Y genes that create an inherent sex bias in the function of XX and XY cells. We propose to use the FCG model to tease apart the effects of sex hormones (testicular or ovarian secretions) vs. sex chromosomes (XX vs. XY genotype) on energy balance, adipose tissue function, glucose and lipid homeostasis, and other aspects of metabolism. Physiological variables will be measured during manipulations of gonadal hormonal levels after gonadectomy and hormone replacement. The X-linked genes that cause sex chromosome effects on obesity will be identified by linkage studies, gene expression, and analysis of transgenic mice. The results will shed light on fundamental sex differences in obesity and metabolic disease, leading to greater understanding of sex-specific factors that ameliorate or exacerbate disease.

Public Health Relevance

Men and women show significant differences in obesity, diabetes, and related metabolic diseases. The proposed research aims to understand the biological origins of such sex differences, especially those differences that are caused by the sex differences in genomic representation of X and Y genes. Understanding the molecular basis of sex differences will shed light on factors that can prevent metabolic disease in both sexes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK083561-04
Application #
8442933
Study Section
Integrative Physiology of Obesity and Diabetes Study Section (IPOD)
Program Officer
Pawlyk, Aaron
Project Start
2010-07-01
Project End
2015-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
4
Fiscal Year
2013
Total Cost
$305,282
Indirect Cost
$107,047
Name
University of California Los Angeles
Department
Physiology
Type
Schools of Arts and Sciences
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Arnold, Arthur P; Cassis, Lisa A; Eghbali, Mansoureh et al. (2017) Sex Hormones and Sex Chromosomes Cause Sex Differences in the Development of Cardiovascular Diseases. Arterioscler Thromb Vasc Biol 37:746-756
Link, Jenny C; Hasin-Brumshtein, Yehudit; Cantor, Rita M et al. (2017) Diet, gonadal sex, and sex chromosome complement influence white adipose tissue miRNA expression. BMC Genomics 18:89
Link, Jenny C; Reue, Karen (2017) Genetic Basis for Sex Differences in Obesity and Lipid Metabolism. Annu Rev Nutr 37:225-245
Reue, Karen (2017) Sex differences in obesity: X chromosome dosage as a risk factor for increased food intake, adiposity and co-morbidities. Physiol Behav 176:174-182
Arnold, Arthur P (2017) Y chromosome's roles in sex differences in disease. Proc Natl Acad Sci U S A 114:3787-3789
Mauvais-Jarvis, Franck; Arnold, Arthur P; Reue, Karen (2017) A Guide for the Design of Pre-clinical Studies on Sex Differences in Metabolism. Cell Metab 25:1216-1230
Arnold, Arthur P (2017) A general theory of sexual differentiation. J Neurosci Res 95:291-300
Arnold, Arthur P; Reue, Karen; Eghbali, Mansoureh et al. (2016) The importance of having two X chromosomes. Philos Trans R Soc Lond B Biol Sci 371:20150113
Burgoyne, Paul S; Arnold, Arthur P (2016) A primer on the use of mouse models for identifying direct sex chromosome effects that cause sex differences in non-gonadal tissues. Biol Sex Differ 7:68
Itoh, Yuichiro; Arnold, Arthur P (2015) Are females more variable than males in gene expression? Meta-analysis of microarray datasets. Biol Sex Differ 6:18

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