Project description:Differences in female and male immunity may contribute to variations in response to infections and predisposition to autoimmunity. The characterization of the mechanisms that drive differential neutrophil phenotypes between genders has been investigated. This provides new insights that distinct sex difference in neutrophil biology related to responses to type I IFNs, immunometabolism and maturation status that may have prominent functional and pathogenic implications. The transcriptome of neutrophils from healthy adult males and females was characterized using bulk RNASeq. The transcriptome of whole blood leukocytes was elucidated using scRNASeq.
Project description:Differences in female and male immunity may contribute to variations in response to infections and predisposition to autoimmunity. The characterization of the mechanisms that drive differential neutrophil phenotypes between genders has been investigated. This provides new insights that distinct sex difference in neutrophil biology related to responses to type I IFNs, immunometabolism and maturation status that may have prominent functional and pathogenic implications. The transcriptome of neutrophils from healthy adult males and females was characterized using bulk RNASeq. The transcriptome of whole blood leukocytes was elucidated using scRNASeq.
Project description:Genome wide DNA methylation profiling of peripheral blood samples. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs. Samples included 63 of male samples,and 54 of female samples from peripheral leukocytes. All samples were healthy controls.
Project description:This project examined if sex differences in K48 polyubiquitination in the amygdala were developmentally regulated. This used basolateral amygdala (BLA) samples collected from 4 and 9 week old male and female Sprague-Dawley rats.
Project description:Epienome-wide DNA methylation profiling of normal human kidney tissue samples. The Illumina HumanMethylation450K Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs in normal human kidney samples. Samples included 15 male and 16 female normal human kidney samples tissue.
Project description:Model dependent on changing parameters.
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal.
The yearly transition probabilities are:
Healthy to Dead: Age/1000; Healthy to Sick: according to function F1 depending on Age and Male parameters; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male parameters. Pre-Transition Rules: Age increased by 1 each cycle.
Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,…,50 for each individual), Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10 and their ages in each state.
Project description:Model with functions depending on Age, Male, BP (Blood Pressure).
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal. The yearly transition probabilities are: Healthy to Dead: Age/1000; Healthy to Sick: According to function F1 depending on Age and Male and BP; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male.
Pre-Transition Rules: Age increased by 1 and BP by Age/10 each simulation cycle. Post-Transition Rules: Treatment = BP>140 , becomes 1 when BP crosses 140 threshold; BP =BP-Treatment*10 , meaning a drop of 10 once treatment is applied; CostThisYear = Age + \Treatment*10 , cost depends on age and if treatment was taken; Cost= Cost + CostThisYear , it accumulates cost over time.
Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,...,50 for each individual), BP =120, Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10 and their ages and costs in each state. A stratified report by male and female and young – up to age 30 and old above age 30 is produced.
Project description:Sex-differences in human liver gene expression were characterized on a genome-wide scale using a large liver sample collection, allowing for detection of small expression differences with high statistical power. 1,249 sex-biased genes were identified, 70% showing higher expression in females. Chromosomal bias was apparent, with female-biased genes enriched on chrX and male-biased genes enriched on chrY and chr19, where 11 male-biased zinc-finger KRAB-repressor domain genes are distributed in six clusters. Top biological functions and diseases significantly enriched in sex-biased genes include transcription, chromatin organization and modification, sexual reproduction, lipid metabolism and cardiovascular disease. Notably, sex-biased genes are enriched at loci associated with polygenic dyslipidemia and coronary artery disease in genome-wide association studies. Moreover, of the 8 sex-biased genes at these loci, 4 have been directly linked to monogenic disorders of lipid metabolism and show an expression profile in females (elevated expression of ABCA1, APOA5 and LDLR; reduced expression of LIPC) that is consistent with the lower female risk of coronary artery disease. Female-biased expression was also observed for CYP7A1, which is activated by drugs used to treat hypercholesterolemia. Several sex-biased drug-metabolizing enzyme genes were identified, including members of the CYP, UGT, GPX and ALDH families. Half of 879 mouse orthologs, including many genes of lipid metabolism and homeostasis, show growth hormone-regulated sex-biased expression in mouse liver, suggesting growth hormone might play a similar regulatory role in human liver. Finally, the evolutionary rate of protein-coding regions for human-mouse orthologs, revealed by dN/dS ratio, is significantly higher for genes showing the same sex-bias in both species than for non-sex-biased genes. These findings establish that human hepatic sex differences are widespread and affect diverse cell metabolic processes, and may help explain sex differences in lipid profiles associated with sex differential risk of coronary artery disease. A first set of randomized liver RNA pools (WS9) was generated by randomly distributing 112 male and 112 female liver RNA samples into 8 pools comprised of 14 male liver samples (pools M1 to M8), and 8 pools of 14 female liver samples each (pools F1 to F8). A second set of 16 pools (WS10) was prepared from the same set of 224 liver samples in the same way (pools M9 to M16 and F9 to F16). The 16 liver RNA pools of each sex were used in a total of 16 male vs. female two-color hybridization microarrays by pairing pool M1 and pool F1, pool M2 with pool F2, etc. Fluorescent labeling of RNA and hybridization of the Alexa 555-labeled and Alexa 647-labeled amplified RNA samples to Agilent Whole Human Genome oligonucleotide microarrays (4 x 44K format; Agilent Technology, Palo Alto, CA; catalog # G4112F) were carried out, with dye swaps to eliminate dye bias.
Project description:Maternal high-fat diet consumption predisposes to metabolic and liver dysfunction in F1 male and female at young adulthood. Purpose: We used RNA-seq to determine the liver transcriptome of male and female F1 of MO and control fed mothers. Methods: Female Wistar rat mothers ate control (C) or obesogenic (MO) diet from the time they were weaned through breeding at postnatal day (PND) 120, delivery and lactation. After weaning all male and female F1 ate control diet. At PND 110 liver and fat were collected to analyze metabolites, histology and liver differentially expressed genes. To identify the functional F1 liver changes due to MO, we evaluated the differentially expressed genes (DEGs) between MO and C males and females with separate pairwise comparisons due to the marked differences between males and females. Genes were filtered based on ≥ 1.4 fold change (FC) and nominal P value <0.05 (Student´s t-test). Results: MOF1 males presented greater physiologic and histological NAFLD characteristics than MOF1 females. RNA-seq revealed 1,365 genes significantly changed in male MOF1 liver and only 70 genes in MOF1 female compared with controls. GO and KEGG analysis identified differentially expressed genes related to metabolic process. Male MOF1 liver showed the following altered pathways: insulin signaling (22 genes), phospholipase D signaling (14 genes), NAFLD (13 genes), and glycolysis/ gluconeogenesis (7 genes). In contrast, few genes were altered in these pathways in MOF1 females. Conclusions: These results improve understanding of the mechanism by which a maternal high fat diet affects their F1. In summary, MO programs sex-dependent F1 changes in insulin, glucose and lipid signaling pathways, leading to liver dysfunction and insulin resistance. Male adult MOF1 livers show global down-regulation of genes that are required for normal function of major liver metabolic pathways. This new knowledge is important for producing sex-specific interventions.
Project description:In this study, we investigated potential sex differences in a Rbm20 knockout mouse model. We used RNA sequencing of bulk RNA from the left ventricle of male and female wildtype and Rbm20 knockout mice.