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1.
Elife ; 112022 02 11.
Article En | MEDLINE | ID: mdl-35147495

Naturally occurring point mutations in the HBG promoter switch hemoglobin synthesis from defective adult beta-globin to fetal gamma-globin in sickle cell patients with hereditary persistence of fetal hemoglobin (HPFH) and ameliorate the clinical severity. Inspired by this natural phenomenon, we tiled the highly homologous HBG proximal promoters using adenine and cytosine base editors that avoid the generation of large deletions and identified novel regulatory regions including a cluster at the -123 region. Base editing at -123 and -124 bp of HBG promoter induced fetal hemoglobin (HbF) to a higher level than disruption of well-known BCL11A binding site in erythroblasts derived from human CD34+ hematopoietic stem and progenitor cells (HSPC). We further demonstrated in vitro that the introduction of -123T > C and -124T > C HPFH-like mutations drives gamma-globin expression by creating a de novo binding site for KLF1. Overall, our findings shed light on so far unknown regulatory elements within the HBG promoter and identified additional targets for therapeutic upregulation of fetal hemoglobin.


Anemia, Sickle Cell/genetics , CRISPR-Cas Systems , Fetal Hemoglobin/genetics , Gene Editing/methods , Adenine/metabolism , Cell Line , Clustered Regularly Interspaced Short Palindromic Repeats , Cytosine/metabolism , Hematopoietic Stem Cells/metabolism , Humans , Point Mutation , Promoter Regions, Genetic , beta-Globins/genetics , beta-Thalassemia/genetics , gamma-Globins/genetics
2.
J Nutr Biochem ; 84: 108441, 2020 10.
Article En | MEDLINE | ID: mdl-32629238

Type 2 diabetes mellitus (T2DM) and insulin resistance (IR) have been associated with dysregulation of iron metabolism. The basis for this association is not completely understood. To attempt to investigate this, we studied temporal associations between onset of insulin resistance (IR) and dysregulated iron homeostasis, in a mouse model of T2DM. Male C57Bl/6 mice (aged 8 weeks) were fed a high-fat diet (HFD; 60% energy from fat) or a control diet (CD; 10% energy from fat) for 4, 8, 12, 16, 20 and 24 weeks. Development of IR was documented, and various metabolic, inflammatory and iron-related parameters were studied in these mice. HFD-feeding induced weight gain, hepato-steatosis and IR in the mice. Onset of IR occurred from 12 weeks onwards. Hepatic iron stores progressively declined from 16 weeks onwards. Accompanying changes included a decrease in hepatic hepcidin (Hamp1) mRNA expression and serum hepcidin levels and an increase in iron content in the epididymal white adipose tissue (eWAT). Iron content in the liver negatively correlated with that in the eWAT. Factors known to regulate hepatic Hamp1 expression (such as serum iron levels, systemic inflammation, and bone marrow-derived erythroid regulators) were not affected by HFD-feeding. In conclusion, the results show that the onset of IR in HFD-fed mice preceded dysregulation of iron homeostasis, evidence of which were found both in the liver and visceral adipose tissue.


Diet, High-Fat/adverse effects , Insulin Resistance , Insulin/metabolism , Iron/metabolism , Adipose Tissue/metabolism , Animals , Diabetes Mellitus, Type 2/metabolism , Homeostasis , Inflammation/metabolism , Liver/metabolism , Male , Mice, Inbred C57BL
3.
Korean J Med Educ ; 31(1): 61-71, 2019 Mar.
Article En | MEDLINE | ID: mdl-30852862

PURPOSE: Students joining medical studies may be motivated by many factors. However, there may also be some factors which may concern them. Although, it can be assumed that those joining medical studies would have largely been influenced positively, how the factors interact in different groups of students has not been studied adequately. METHODS: We conducted a questionnaire-based survey in first-year medical students. Besides the demographics and intentions about their future career plans, students rated a list of positively influencing items and a list of negatively affecting items relevant to our context that influenced their decision. We performed factor analysis followed by clustering of study participants. RESULTS: Ninety-seven students participated in the survey which comprised of 59% females with mean age of 18.6 years. The factors extracted were named as 'personal growth factor,' 'professional calling factor,' 'personal concerns factor,' and 'professional concerns factor.' Four distinct clusters of participants differing in their average ratings to each of the above factors were identified. CONCLUSION: This study provides information on the factors that influence students to join medical studies from an Indian context. The motivational patterns were varied in different sub-groups of students. The data obtained from this study may provide pointers to educators to plan training of students, changes in curricular structure that takes into account the expansion of medical education into specialties and beyond.


Career Choice , Education, Medical , Motivation , Students, Medical , Adolescent , Adult , Factor Analysis, Statistical , Female , Humans , India , Male , Sex Factors , Surveys and Questionnaires , Young Adult
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