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Diabetes Mellitus: Type 2 and Gestational01:22

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Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
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Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia. The four categories of diabetes are type 1 diabetes, type 2 diabetes, other specific types of diabetes, and gestational diabetes.
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Incomplete Dominance01:43

Incomplete Dominance

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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
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Updated: May 22, 2025

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq
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Type 1 Diabetes Genetics Consortium.

Suna Onengut-Gumuscu1, Patrick Concannon2, Beena Akolkar3

  • 1Department of Genome Sciences, The University of Virginia, Charlottesville, VA 22908, USA.

The Journal of Clinical Endocrinology and Metabolism
|March 21, 2025
PubMed
Summary
This summary is machine-generated.

The Type 1 Diabetes Genetics Consortium discovered over 100 genetic loci linked to Type 1 diabetes (T1D) risk. This research identified noncoding variations and autoimmune pathways, offering new targets for T1D prediction, prevention, and treatment.

Keywords:
associationfine mappinggeneticslinkagetype 1 diabetes

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Area of Science:

  • Genetics
  • Immunology
  • Endocrinology

Background:

  • Type 1 diabetes (T1D) arises from autoimmune destruction of insulin-producing beta cells, with genetics contributing ~50% of risk.
  • Limited understanding of T1D genetic basis existed before the Type 1 Diabetes Genetics Consortium (T1DGC).

Purpose of the Study:

  • To accelerate the discovery of genes contributing to T1D risk.
  • To highlight the T1DGC's contributions to understanding T1D's genetic basis.

Main Methods:

  • Established the Type 1 Diabetes Genetics Consortium (T1DGC) in 2002.
  • Utilized family-based linkage and case-control genome-wide association studies.
  • Conducted large-scale genetic research and fine mapping to define risk regions.

Main Results:

  • Discovered over 100 loci associated with T1D risk, many with small effects.
  • Identified noncoding genetic variations in disease-relevant cell types contributing to T1D etiology.
  • Made data, results, and samples available to the scientific community.

Conclusions:

  • The T1DGC significantly expanded the known genetic factors contributing to T1D risk.
  • Research identified novel autoimmune pathways and genetic variants for T1D.
  • Findings provide new targets for T1D prediction, prevention, and treatment.