ID

46158

Descrição

Principal Investigator: Richard Gibbs, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA MeSH: Psoriasis,Arthritic psoriasis https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000766 The GEI Studies Project was started as an NIH consortium involving 5 disease groups with funding provided through the Genes, Environment, and Health Initiative (GEI). The objective of the project was to optimize strategies for identifying rare variants as a follow up to genome-wide association studies (GWAS) using next-generation sequencing technology. One of the five targeted diseases, Psoriasis, is a multifactorial skin disease characterized by epidermal hyperproliferation and chronic inflammation that affects approximately 2% of Americans. Because only about one-third of all patients with psoriasis have a relative who is also affected with the disorder, psoriasis is not widely recognized as a genetic disease. However, previous research on families and identical twins has shown psoriasis has a strong genetic component, although environmental factors (such as infections, stress, and injuries) are also important. Although no definite psoriasis gene has yet been identified, research during the last ten years has revealed over forty potential gene locations that may contribute to the disease. Large amounts of data generated using next-generation sequencing technology would provide a more detailed characterization of sequence variation which would in turn increase the likelihood of detecting causative loci. With the presumption that rare variants are frequently the cause of a large portion of phenotypic variation, it was necessary to use large sample sets. In the main body of this study, we sequenced 4,966 samples (812 dermatologist-diagnosed cases of purely cutaneous psoriasis (PsC), 1,497 cases of rheumatologist-diagnosed psoriatic arthritis, 665 cases of cutaneous psoriasis with uncertain psoriatic arthritis status (PsV) and 1,992 controls) across 5.7 Mb of sequence containing 100 psoriasis candidate loci and 769 genes. For each candidate locus, we considered sequences within 250 kb of the strongest association signal. Within this window, three strategies were employed. For ten of the strongest psoriasis signals, we used a whole-region approach which included non-coding intergenic and intronic sequence. For four established loci of lesser significance, we targeted all full transcription units within the +/- 250 kb interval. For the remaining signals, we targeted the exons of all transcription units within the +/- 250 kb interval. Due to complexities of high-efficiency targeting of HLA genes we selected 5 specific candidate genes for sequencing near the HLA-C gene.

Link

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000766

Palavras-chave

  1. 01/02/2023 01/02/2023 - Dr. med. Lucy Kessler
  2. 29/01/2025 29/01/2025 - Akane Nishihara
Titular dos direitos

Richard Gibbs, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA

Transferido a

29 de janeiro de 2025

DOI

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Licença

Creative Commons BY 4.0

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dbGaP phs000766 GEI Studies - Psoriasis

The dataset provides gender information.

pht003940
Descrição

pht003940

De-identified Subject ID
Descrição

SUBJID

Tipo de dados

string

Alias
UMLS CUI [1,1]
C4684638
UMLS CUI [1,2]
C2348585
Gender of participant
Descrição

gender

Tipo de dados

text

Alias
UMLS CUI [1,1]
C0079399

Similar models

The dataset provides gender information.

Name
Tipo
Description | Question | Decode (Coded Value)
Tipo de dados
Alias
Item Group
pht003940
SUBJID
Item
De-identified Subject ID
string
C4684638 (UMLS CUI [1,1])
C2348585 (UMLS CUI [1,2])
Item
Gender of participant
text
C0079399 (UMLS CUI [1,1])
Code List
Gender of participant
CL Item
Female (F)
C0086287 (UMLS CUI [1,1])
CL Item
Male (M)
C0086582 (UMLS CUI[1,1])
CL Item
Unknown (UNK)
C0439673 (UMLS CUI [1,1])

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