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>

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>

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 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

Abstract P068: A Genome-wide Association Study for Diabetic Nephropathy Genes in the Japanese Population: The J-MICC Study.

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Yasuyuki Nakamura ◽  
Akira Narita ◽  
Seiko Ohno ◽  
Naoyuki Takashima ◽  
Kenji Wakai ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Japanese Population ◽  
Association Studies ◽  
Linear Regression Analysis ◽  
Genotype Imputation ◽  
Genome Wide Association ◽  
Diabetic Patients ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Background: Diabetic nephropathy is the most common cause of chronic kidney disease in the developed countries. Clinical characteristics do not fully predict development of diabetic nephropathy in diabetic patients. There have been few genome-wide association studies (GWAS). Methods: We conducted a GWAS to identify common genetic variations that affected renal function in a Japanese population of 1,117 patients with type 2 diabetes mellitus (T2D) extracted from 14,091 participants appropriate for GWAS as a part of the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. Genotyping was performed at a central laboratory using a HumanOmniExpressExome-8 v1.2 BeadChip array. Genotype imputation was performed using SHAPEIT and Minimac3 software based on the 1000 Genomes reference panel (phase 3). Estimated glomerular filtration rate (eGFR) was calculated according to Matsuo et al. for each patient. The association for the imputed variants with eGFR was performed by a linear regression analysis adjusted for age and sex. Results: We found that rs869312667 at NBEA (β=1.23, P=1.03E-08) and rs8523 at ELOVL2 (β=24.4, P=1.64E-08) were significantly associated with eGFR. These genes have been reported to participate in several metabolic functions and were associated with some disease conditions. However, no previous reports have implied that these genes were related to diabetic nephropathy. Conclusions: rs869312667 at NBEA and rs8523 at ELOVL2 were significantly associated with eGFR in patients with T2D in Japanese.

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 Power Analysis Provides Bounds for Genetic Architecture and Insights to Challenges for Rare Variant Association Studies

2017 ◽  
Author(s):  
Andriy Derkach ◽  
Haoyu Zhang ◽  
Nilanjan Chatterjee
Keyword(s):  
Power Analysis ◽  
Genetic Architecture ◽  
Rare Variants ◽  
Association Studies ◽  
Power Calculation ◽  
Genome Wide Association Studies ◽  
Meaningful Improvement ◽  
Association Tests ◽  
Genome Wide ◽  
A Genome

AbstractGenome-wide association studies are now shifting focus from analysis of common to uncommon and rare variants with an anticipation to explain additional heritability of complex traits. As power for association testing for individual rare variants may often be low, various aggregate level association tests have been proposed to detect genetic loci that may contain clusters of susceptibility variants. Typically, power calculations for such tests require specification of large number of parameters, including effect sizes and allele frequencies of individual variants, making them difficult to use in practice. In this report, we approximate power to varying degree of accuracy using a smaller number of key parameters, including the total genetic variance explained by multiple variants within a locus. We perform extensive simulation studies to assess the accuracy of the proposed approximations in realistic settings. Using the simplified power calculation methods, we then develop an analytic framework to obtain bounds on genetic architecture of an underlying trait given results from a genome-wide study and observe important implications for the completely lack of or limited number of findings in many currently reported studies. Finally, we provide insights into the required quality of annotation/functional information for identification of likely causal variants to make meaningful improvement in power of subsequent association tests. A shiny application, Power Analysis for GEnetic AssociatioN Tests (PAGEANT), in R implementing the methods is made publicly available.

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. 

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