Article

Pancreatic autoantibodies, HLA DR and PTPN22 polymorphisms in first degree relatives of patients with type 1 diabetes and multiethnic background.

Nutrology Section, Universidade Federal do Rio de Janeiro, Rio de Janeiro/RJ, Brazil.
Experimental and Clinical Endocrinology &amp Diabetes (impact factor: 1.69). 11/2011; 119(10):618-20. DOI:10.1055/s-0031-1280799 pp.618-20
Source: PubMed

ABSTRACT To evaluate the prevalence of pancreatic auto-antibodies (PAb) as well as its relationship with HLA DR B1 and PTPN22 polymorphisms in first degree relatives (FDR) of Brazilian patients with Type 1 diabetes (T1D) and multiethnic background.
FDR of patients with T1D were interviewed and blood was sampled for PAb measurement, HLA DRB1 and PTPN22 genotyping. Genotyping was also performed in index cases.
In FDR (n=78), 16.7% presented at least one PAb. These individuals had a higher prevalence of HLA DRB1* 03 than others (p=0.03), without differences in PTPN22 genotyping. While the genetic profile was similar in FDR with PAb and their index cases, those without PAb had a lower frequency of HLA DR B1 * 03 than their correspondent patients (p=0.009).
In this multiethnic population, a significant proportion of FDR of T1D patients had PAb, which was associated with HLA DR B1 * 03 but not with the PTPN22 polymorphism.

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    Article: Improving power of genome-wide association studies with weighted false discovery rate control and prioritized subset analysis.
    Wan-Yu Lin, Wen-Chung Lee
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    ABSTRACT: The issue of large-scale testing has caught much attention with the advent of high-throughput technologies. In genomic studies, researchers are often confronted with a large number of tests. To make simultaneous inference for the many tests, the false discovery rate (FDR) control provides a practical balance between the number of true positives and the number of false positives. However, when few hypotheses are truly non-null, controlling the FDR may not provide additional advantages over controlling the family-wise error rate (e.g., the Bonferroni correction). To facilitate discoveries from a study, weighting tests according to prior information is a promising strategy. A 'weighted FDR control' (WEI) and a 'prioritized subset analysis' (PSA) have caught much attention. In this work, we compare the two weighting schemes with systematic simulation studies and demonstrate their use with a genome-wide association study (GWAS) on type 1 diabetes provided by the Wellcome Trust Case Control Consortium. The PSA and the WEI both can increase power when the prior is informative. With accurate and precise prioritization, the PSA can especially create substantial power improvements over the commonly-used whole-genome single-step FDR adjustment (i.e., the traditional un-weighted FDR control). When the prior is uninformative (true disease susceptibility regions are not prioritized), the power loss of the PSA and the WEI is almost negligible. However, a caution is that the overall FDR of the PSA can be slightly inflated if the prioritization is not accurate and precise. Our study highlights the merits of using information from mounting genetic studies, and provides insights to choose an appropriate weighting scheme to FDR control on GWAS.
    PLoS ONE 01/2012; 7(4):e33716. · 4.09 Impact Factor
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Keywords

Brazilian patients
 
correspondent patients
 
FDR
 
first degree relatives
 
genetic profile
 
HLA DR B1
 
HLA DRB1
 
lower frequency
 
multiethnic background
 
multiethnic population
 
one PAb
 
PAb
 
PAb measurement
 
patients
 
PTPN22 genotyping
 
PTPN22 polymorphism
 
PTPN22 polymorphisms
 
significant proportion
 
T1D patients
 
Type 1 diabetes