scholarly journals Fine Mapping and Functional Studies of Risk Variants for Type 1 Diabetes at Chromosome 16p13.13

Diabetes ◽  
2014 ◽  
Vol 63 (12) ◽  
pp. 4360-4368 ◽  
Author(s):  
M. J. Tomlinson ◽  
A. Pitsillides ◽  
R. Pickin ◽  
M. Mika ◽  
K. L. Keene ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Fine Mapping ◽  
Functional Studies ◽  
Risk Variants

scholarly journals Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes

2018 ◽  
Vol 50 (10) ◽  
pp. 1366-1374 ◽  
Author(s):  
Harm-Jan Westra ◽  
Marta Martínez-Bonet ◽  
Suna Onengut-Gumuscu ◽  
Annette Lee ◽  
Yang Luo ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Type 1 Diabetes ◽  
Fine Mapping ◽  
Functional Studies ◽  
Causal Variants

Functional Evaluation of RNLS, a Gene Harboring Risk Variants for Type 1 Diabetes in European and African Ancestry Subjects

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1702-P
Author(s):  
SUNA ONENGUT-GUMUSCU ◽  
NOAH VOGLER ◽  
MARIA FAIDAS ◽  
REBECCA R. PICKIN ◽  
ELAINE GERSZ ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
African Ancestry ◽  
Functional Evaluation ◽  
Risk Variants

scholarly journals De‐ coding genetic risk variants in type 1 diabetes

2021 ◽  
Author(s):  
Melanie R Shapiro ◽  
Puchong Thirawatananond ◽  
Leeana Peters ◽  
Robert C Sharp ◽  
Similoluwa Ogundare ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Genetic Risk ◽  
Risk Variants ◽  
Genetic Risk Variants

The state of the vegetative nervous system, characteristics of muscular electrogenesis, peripheral hemodynamics, and their changes under the influence of the procedure of hydrodynamic tablet therapy (HDTT) in the children presenting with type 1 diabetes mellitus

2016 ◽  
Vol 15 (3) ◽  
pp. 120-124
Author(s):  
N. V Lagunova ◽  
T. F Golubova ◽  
Irina Anatol’evna Polenok ◽  
A. V Kurganova
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetic Polyneuropathy ◽  
The State ◽  
Bioelectrical Activity ◽  
Health Resort ◽  
Vegetative Nervous System ◽  
Functional Studies

The clinical, neurological, and functional studies in the children suffering from type 1 diabetes mellitus have demonstrated that practically every fourth patient presented with the complaints and symptoms of this pathology associated with the development of diabetic polyneuropathy, the reduced bioelectrical activity, and the changes of peripheral blood circulation strongly depending on the duration and the quality of compensation of the disease. Under the influence of the treatment under the conditions of a spa and health resort facility with the inclusion of hydrodynamic tablet therapy, the positive dynamics of the parameters of interest was documented in the form of the improvement of the state of carbohydrate metabolism, clinical and neurological characteristics, and the effectiveness of the functional methods for the examination of the children presenting with type 1 diabetes.

scholarly journals A multi-task convolutional deep learning method for HLA allelic imputation and its application to trans-ethnic MHC fine-mapping of type 1 diabetes

2020 ◽  
Author(s):  
Tatsuhiko Naito ◽  
Ken Suzuki ◽  
Jun Hirata ◽  
Yoichiro Kamatani ◽  
Koichi Matsuda ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Deep Learning ◽  
Fine Mapping ◽  
Low Frequency ◽  
Amino Acid Position ◽  
Genotype Imputation ◽  
Learning Method ◽  
Frequency Spectra ◽  
Shared Risk

Conventional HLA imputation methods drop their performance for infrequent alleles, which reduces reliability of trans-ethnic MHC fine-mapping due to inter-ethnic heterogeneity in allele frequency spectra. We developed DEEP*HLA, a deep learning method for imputing HLA genotypes. Through validation using the Japanese and European HLA reference panels (n = 1,118 and 5,112), DEEP*HLA achieved the highest accuracies in both datasets (0.987 and 0.976) especially for low-frequency and rare alleles. DEEP*HLA was less dependent of distance-dependent linkage disequilibrium decay of the target alleles and might capture the complicated region-wide information. We applied DEEP*HLA to type 1 diabetes GWAS data of BioBank Japan (n = 62,387) and UK Biobank (n = 356,855), and successfully disentangled independently associated class I and II HLA variants with shared risk between diverse populations (the top signal at HLA-DRβ1 amino acid position 71; P = 6.2 × 10-119). Our study illustrates a value of deep learning in genotype imputation and trans-ethnic MHC fine-mapping.

scholarly journals Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers

2015 ◽  
Vol 47 (4) ◽  
pp. 381-386 ◽  
Author(s):  
Suna Onengut-Gumuscu ◽  
◽  
Wei-Min Chen ◽  
Oliver Burren ◽  
Nick J Cooper ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Fine Mapping ◽  
Susceptibility Loci ◽  
Diabetes Susceptibility ◽  
Causal Variants

scholarly journals Fine mapping of type 1 diabetes regions Idd9.1 and Idd9.2 reveals genetic complexity

2013 ◽  
Vol 24 (9-10) ◽  
pp. 358-375 ◽  
Author(s):  
Emma E. Hamilton-Williams ◽  
Daniel B. Rainbow ◽  
Jocelyn Cheung ◽  
Mikkel Christensen ◽  
Paul A. Lyons ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Fine Mapping ◽  
Genetic Complexity

1697-P: Functional Impact of Type 1 Diabetes Risk Variants Identified in African- and European-Ancestry Populations

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1697-P
Author(s):  
SUNA ONENGUT ◽  
HANZHI YANG ◽  
REBECCA R. PICKIN ◽  
STEPHEN S. RICH
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Risk ◽  
European Ancestry ◽  
Functional Impact ◽  
Risk Variants

scholarly journals Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

2021 ◽  
Author(s):  
Catherine C. Robertson ◽  
Jamie R. J. Inshaw ◽  
Suna Onengut-Gumuscu ◽  
Wei-Min Chen ◽  
David Flores Santa Cruz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Fine Mapping ◽  
Drug Targets ◽  
Genomic Analyses ◽  
Causal Variants

scholarly journals Statistical colocalization of monocyte gene expression and genetic risk variants for type 1 diabetes

2012 ◽  
Vol 21 (12) ◽  
pp. 2815-2824 ◽  
Author(s):  
Chris Wallace ◽  
Maxime Rotival ◽  
Jason D. Cooper ◽  
Catherine M. Rice ◽  
Jennie H.M. Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Type 1 Diabetes ◽  
Genetic Risk ◽  
Risk Variants ◽  
Genetic Risk Variants
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