Publications by authors named "S Kobes"

Genetic determinants of interindividual differences in energy expenditure (EE) are largely unknown. Sphingolipids, such as ceramides, have been implicated in the regulation of human EE via mitochondrial uncoupling. In this study, we investigated whether genetic variants within enzymes involved in sphingolipid synthesis and degradation affect EE and insulin-related traits in a cohort of American Indians informative for 24-h EE and glucose disposal rates during a hyperinsulinemic-euglycemic clamp.

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Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007.

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Article Synopsis
  • - This study explores how growth patterns during puberty relate to future health outcomes by analyzing height data from about 56,000 individuals across various ancestries using a technique called SITAR.
  • - The researchers identified 26 significant genetic loci linked to height growth during puberty and found that different growth rates are associated with various health risks, like type 2 diabetes and heart conditions.
  • - The findings suggest that there are multiple growth trajectories during puberty, each influencing adult health differently, indicating that no single growth pattern is the "best" for lifelong health outcomes.
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Early puberty onset is associated with higher risk of diabetes, but most studies have not accounted for childhood factors that may confound the association. Using data from a study conducted in an Indigenous community in Arizona (1965-2007), we examined associations of timing and velocity of the adolescent growth spurt with type 2 diabetes, and whether these associations are mediated by childhood body mass index and insulinemia. Adolescent growth parameters were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, for 861 participants with height measurements spanning the whole period of growth.

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