scholarly journals Genes Expression in Type 1 Diabetes: An Update

2019 ◽  
Vol 6 (2) ◽  
pp. 4327-4331
Author(s):  
Dr. Kishore Kumar Soni ◽  
Dr. Sushil Singh
Keyword(s):  
Type 1 Diabetes ◽  
Association Studies ◽  
Disease Onset ◽  
Genome Wide Association Studies ◽  
Autoimmune Destruction ◽  
Disease Biology ◽  
Genome Wide ◽  
Genes Expression ◽  
Practical Effect

Type 1 Diabetes (T1D) is autoimmune disease with a sturdy genetic component, which, through interactions with particular environmental factors, causes disease onset. T1D usually reveals in early to mid-childhood through the autoimmune destruction of pancreatic cells resulting in a lack of insulin production. Traditionally, prior to genome-wide association studies (GWAS), six loci in the genome were fully established to be associated with T1D. The originations of genetic factors involved in T1D through GWAS present the first step in a long process leading to cure. Genes uncovered using this approach is indeed necessary to disease biology and will define the key molecular pathways leading to cure of T1D. However, such genome wide scans can lack coverage in certain regions where it is difficult to , thus, it is possible that other loci with practical effect sizes remain to be uncovered through whole genome sequencing approaches. In this review, we address recent expansions in the genetics of T1D and provide an update on the latest predisposition loci added to the list of genes involved in the of T1D

scholarly journals Meta-genome-wide association studies identify a locus on chromosome 1 and multiple variants in the MHC region for serum C-peptide in type 1 diabetes

Diabetologia ◽  
2018 ◽  
Vol 61 (5) ◽  
pp. 1098-1111 ◽  
Author(s):  
Delnaz Roshandel ◽  
◽  
Rose Gubitosi-Klug ◽  
Shelley B. Bull ◽  
Angelo J. Canty ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Association Studies ◽  
Genome Wide Association ◽  
Chromosome 1 ◽  
Genome Wide Association Studies ◽  
C Peptide ◽  
Genome Wide ◽  
Multiple Variants

scholarly journals Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e78577 ◽  
Author(s):  
Finja Büchel ◽  
Florian Mittag ◽  
Clemens Wrzodek ◽  
Andreas Zell ◽  
Thomas Gasser ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Type 1 Diabetes ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes

PLoS Genetics ◽  
2009 ◽  
Vol 5 (10) ◽  
pp. e1000678 ◽  
Author(s):  
Zhi Wei ◽  
Kai Wang ◽  
Hui-Qi Qu ◽  
Haitao Zhang ◽  
Jonathan Bradfield ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Type 1 Diabetes ◽  
Association Studies ◽  
Disease Association ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals New Genes and Emerging Mechanisms of Type 1 Diabetes

2021 ◽  
Vol 2 (2) ◽  
pp. 47-51
Author(s):  
Aysha Karim Kiani ◽  
Asima Zia ◽  
Parveen Akhtar ◽  
Sadaf Moeez ◽  
Attya Bhatti ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Diabetes Susceptibility ◽  
Multiple Loci ◽  
New Genes ◽  
Genome Wide ◽  
Gwa Studies

Type 1 Diabetes susceptibility depends upon the complex interaction between numerous genetic as well as environmental factors. 50% of the familial clustering of T1D is explained by HLA locus alleles. Other multiple loci contribute the rest of the susceptibility, in which very little were known since last few years. Four novel loci were found from the results of stage-I, genome wide association (GWA) studies which were carried out with high-density genotyping arrays. As the stage-II of the Genome Wide Association studies completed, hopefully, most of the genetic reasons of Type 1 Diabetes will be identified. 

scholarly journals Bootstrap Distillation: Non-parametric Internal Validation of GWAS Results by Subgroup Resampling

2017 ◽  
Author(s):  
David A. Eccles ◽  
Rodney A. Lea ◽  
Geoffrey K. Chambers
Keyword(s):  
Type 1 Diabetes ◽  
Association Studies ◽  
Sampling Technique ◽  
Genome Wide Association ◽  
Frequency Variation ◽  
Genome Wide Association Studies ◽  
Internal Validation ◽  
Genotype Frequencies ◽  
Genome Wide

AbstractGenome-wide Association Studies are carried out on a large number of genetic variants in a large number of people, allowing the detection of small genetic effects that are associated with a trait. Natural variation of genotypes within populations means that any particular sample from the population may not represent the true genotype frequencies within that population. This may lead to the observation of marker-disease associations when no such association exists.A bootstrap population sub-sampling technique can reduce the influence of allele frequency variation in producing false-positive results for particular samplings of the population. In order to utilise bioinformatics in the service of a serious disease, this sub-sampling method has been applied to the Type 1 Diabetes dataset from the Wellcome Trust Case Control Consortium in order to evaluate its effectiveness.While previous literature on Type 1 Diabetes has identified some DNA variants that are associated with the disease, these variants are not informative for distinguishing between disease cases and controls using genetic information alone (AUC=0.7284). Population sub-sampling filtered out noise from genome-wide association data, and increased the chance of finding useful associative signals. Subsequent filtering based on marker linkage and testing of marker sets of different sizes produced a 5-SNP signature set of markers for Type 1 Diabetes. The group-specific markers used in this set, primarily from the HLA region on chromosome 6, are considerably more informative than previously known associated variants for predicting T1D phenotype from genetic data (AUC=0.8395). Given this predictive quality, the signature set may be useful alone as a screening test, and would be particularly useful in combination with other clinical cofactors for Type 1 Diabetes risk.

scholarly journals Novel Linkage Peaks Discovered for Diabetic Nephropathy in Individuals With Type 1 Diabetes

2021 ◽  
Author(s):  
Jani Haukka ◽  
Niina Sandholm ◽  
Erkka Valo ◽  
Carol Forsblom ◽  
Valma Harjutsalo ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetic Nephropathy ◽  
Rare Variants ◽  
Association Studies ◽  
Linkage Study ◽  
Study Cohort ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Genome-wide association studies (GWAS) and linkage studies have had only limited success in discovering genome-wide significantly linked regions or risk loci for diabetic nephropathy in individuals with type 1 diabetes (T1D). As GWAS cohorts have grown, they have also included more documented and undocumented familial relationships. Here, we computationally inferred and manually curated pedigrees in a study cohort of more than 6,000 individuals with T1D and their non-diabetic relatives. We performed linkage study for 177 pedigrees consisting of 452 individuals with T1D and their relatives using a genome- wide genotyping array with more than 300,000 SNPs and the PSEUDOMARKER software. The analysis resulted in genome-wide significant linkage peaks on eight chromosomal regions from five chromosomes (logarithm of odds [LOD]>3.3). The highest peak was localized at the HLA region on chromosome 6p, but whether the peak originates from T1D or diabetic nephropathy, remains ambiguous. Of the other significant peaks, the chromosome 4p22 region is localized on top of a gene associated with focal segmental glomerulosclerosis, <i>ARHGAP24</i>, suggesting that the gene may play a role in diabetic nephropathy as well. Furthermore, rare variants have been associated with diabetic nephropathy and chronic kidney disease near the 4q25 peak, localized on top of <i>CCSER1</i>. <br>

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