BackgroundHost 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.Materials and MethodsStudy cohort consists of 97 mice from 2 CC lines (both sexes), maintained on either HFD or Standard diet (CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) bacteria (control groups without infection). Body weight (BW) and glucose tolerance ability were assessed at the end time point of the experiment.ResultsThe CC lines varied (P < .05) at their BW gain and glucose tolerance ability (with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females (both lines) were deteriorated in response to infection.ConclusionsThis study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

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. We aimed to study the multimorbidity of IC, T2D, and obesity using CC lines, measuring their responses to HFD and oral bacterial infection. The study used 63 mice of both sexes generated from two CC lines (IL557 and IL711). For 12 weeks, experimental mice were maintained on specific dietary regimes combined with co‐infection with oral bacteria Porphyromonas gingivalis and Fusobacterium nucleatum, while control groups were not infected. Body weight (BW) and results of a intraperitoneal glucose tolerance test (IPGTT) were recorded at the end of 12 weeks, after which length and size of the intestines were assessed for polyp counts. Results Polyp counts ranged between 2 and 10 per CC line. The combination of HFD and infection significantly reduced (P < .01) the colon polyp size of IL557 females to 2.5 cm2, compared to the other groups. Comparing BW gain, IL557 males on HFD gained 18 g, while the females gained 10 g under the same conditions and showed the highest area under curve (AUC) values of 40 000‐45 000 (min mg/dL) in the IPGTT. Conclusion The results show that mice from different genetic backgrounds respond differently to a high fat diet and oral infection in terms of polyp development and glucose tolerance, and this effect is gender related.

Background: Type 2 diabetes (T2D) is a metabolic disease with an imbalance in blood glucose concentration. There are significant studies currently showing association between T2D and intestinal cancer developments. High fat diet (HFD) plays part in the disease development of T2D, intestinal cancer, and infectious diseases through many biological mechanisms, including, but not limited to inflammation. Understanding the systems genetics of the multimorbidity of these diseases will provide an important knowledge and platform for dissecting the complexity of these diseases. Furthermore, in this study we used some machine learning (ML) models to explore more aspects of diabetes mellitus.Aims: The ultimate aim of this project is to study the genetic factors, which underline T2D development, associated with intestinal cancer in response to a HFD consumptions and oral co-infection, jointly or separately, on the same host genetic background. Materials & Methods: A cohort of 307 mice of eight different CC mouse lines in the four experimental groups was assessed. The mice were maintained on either HFD or Chow diet (CHD) for 12 weeks period, while half of each dietary group was either co-infected with oral bacteria or un-infected. Host response to a glucose load and clearance was assessed using intraperitoneal glucose tolerance test (IPGTT) at two time points (weeks 6 and 12) during the experiment period and, subsequently was translated to area under curve (AUC) values. At week 5 of the experiment, mice of group two and four were co-infected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) strains, three times a week, while keeping the other uninfected mice as a control group. At week 12, mice were sacrificed, small intestines and colon were extracted and subsequently the Polyp counts assessed, as well the intestine lengths and size measured. Results & conclusions: Our results have shown that there is a significant variation in polyp's number in different CC lines, with a spectrum between 2.5 and 12.8 total polyps on average. There was a significant correlation between area under curve (AUC) and intestine measurements, including polyp counts, length and size. In addition, our results have shown a significant sex-effect on polyp development and glucose tolerance ability with males more susceptible to HFD than females by showing higher AUC in the glucose tolerance test. The ML results showed that classification with random forest could reach the highest accuracy when all the attributes were used.These results provide an excellent platform for proceeding towards understanding the nature of the genes involved in resistance and rate of development of intestinal cancer and T2D induced by HFD and oral co-infection. Once obtained, such data can be used to predict individual risk for developing these diseases and to establish the genetically based strategy for their prevention and treatment.