Publications by authors named "Hanifa Abu Toamih Atamni"

A chronic metabolic illness, type 2 diabetes (T2D) is a polygenic and multifactorial complicated disease. With an estimated 463 million persons aged 20 to 79 having diabetes, the number is expected to rise to 700 million by 2045, creating a significant worldwide health burden. Polygenic variants of diabetes are influenced by environmental variables.

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Background: Familial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated Apc (Multiple intestinal neoplasia), develop intestinal adenomas.

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Background: Multimorbidity of intestinal cancer (IC), type 2 diabetes (T2D) and obesity is a complex set of diseases, affected by environmental and genetic risk factors. High-fat diet (HFD) and oral bacterial infection play important roles in the etiology of these diseases through inflammation and various biological mechanisms.

Methods: To study the complexity of this multimorbidity, we used the collaborative cross (CC) mouse genetics reference population.

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Article Synopsis
  • The Collaborative Cross (CC) mouse population helps scientists study how genes affect things like obesity, which is influenced by both genes and the environment.
  • Researchers created a new automated process to look at these genetic factors and how they relate to diet-induced obesity in different mice.
  • They found that male and female mice respond differently to a high-fat diet, showing that genetics and obesity can be influenced in distinct ways based on sex, which needs more study.
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Background: Host genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes (T2D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross (CC), for dissecting host susceptibility for the development of T2D and obesity, showing significant variations following high-fat (42% fat) diet (HFD). Here, we aimed to assessing the host genetic background and sex effects on T2D and obesity development in response to oral-mixed bacterial infection and HFD using the CC lines.

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The Collaborative Cross (CC) mouse model is a next-generation mouse genetic reference population (GRP) designated for a high-resolution quantitative trait loci (QTL) mapping of complex traits during health and disease. The CC lines were generated from reciprocal crosses of eight divergent mouse founder strains composed of five classical and three wild-derived strains. Complex traits are defined to be controlled by variations within multiple genes and the gene/environment interactions.

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The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions.

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Background: Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.

Methods: Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an electronic balance.

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Background: Animal models for neurodevelopmental disorders (NDD) generally rely on a single genetic mutation on a fixed genetic background. Recent human genetic studies however indicate that a clinical diagnosis with ASDAutism Spectrum Disorder (ASD) is almost always associated with multiple genetic fore- and background changes. The translational value of animal model studies would be greatly enhanced if genetic insults could be studied in a more quantitative framework across genetic backgrounds.

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Infectious diseases, also known as communicable diseases, refer to a full range of maladies caused by pathogen invasion to the host body. Host response towards an infectious pathogen varies between individuals, and can be defined by responses from asymptomatic to lethal. Host response to infectious pathogens is considered as a complex trait controlled by gene-gene (host-pathogen) and gene-environment interactions, leading to the extensive phenotypic variations between individuals.

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Background: High-fat diet (HFD), body weight (BW) gain, and impaired glucose tolerance development are associated with alveolar bone loss (ABL) in susceptible individuals. This report explores the Collaborative Cross (CC) mouse population for studying the impact of genetic background on comorbidity of alveolar bone change and glucose tolerance after HFD consumption.

Methods: Seventy-eight mice from 19 different CC lines were maintained on rodent chow diet for 8 weeks and were subsequently transferred to an HFD (42% fat) for an additional 12 weeks.

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Type-2 diabetes (T2D) is a complex metabolic disease characterized by impaired glucose tolerance. Despite environmental high risk factors, host genetic background is a strong component of T2D development. Herein, novel highly genetically diverse strains of collaborative cross (CC) lines from mice were assessed to map quantitative trait loci (QTL) associated with variations of glucose-tolerance response.

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Article Synopsis
  • The Collaborative Cross (CC) mouse model offers a unique opportunity to study how genetic variation affects drug responses due to its extensive genetic diversity and reproducibility.
  • Researchers conducted RNA-sequencing on livers from 29 CC lines to analyze gene expression and its relation to drug metabolism, focusing on expression quantitative trait loci (eQTLs).
  • The study revealed significant genetic influences on drug biotransformation and clarified the relationship between drug metabolism and lipid metabolism, providing valuable insights for future pharmacogenomic research.
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