Epigenetic biomarkers to predict psoriasis disease progression * towards tailored therapy.

Epigenetic biomarkers to predict psoriasis disease progression * towards tailored therapy. - Psoriasis Epigenetics

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

NL-OMON

Registry ID

NL-OMON40335

Enrollment

Registered

2014-05-19

Start date

2014-07-20

Completion date

Unknown

Last updated

2024-04-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

psoriasis skin disease with fast proliferation and less differentiation of skin cells

Interventions

None listed

Eligibility

Age

18 Years to 99 Years

Inclusion criteria

Inclusion criteria: For psoriasis patients: - Age: >18 years old - No systemic therapy for psoriasis - Clinical diagnosis: Psoriasis Vulgaris or Psoriasis Guttata (The diagnosis will be confirmed by a dermatologist) - Topical therapy is OK if it IS possible to stop for 3 weeks;For the control group: - Age: >18 years old - No generalised skin disease

Exclusion criteria

Exclusion criteria: For psoriasis patients: - Age:

Design outcomes

Primary

Measure	Time frame
The main study parameter is the sequence of DNA-methylation status (methylome) of the patient material. From these sequences a top set of genes (defined from differential methylation) will be defined that most reliably (r >=0.95, FDR	—

Secondary

Measure	Time frame
Secondary study parameter is the full transcriptome of the patient material. We will use this data to determine whether the methylation patterns that we find affect gene expression. Biomarkers of necessity reflect disease processes that are correlated to a particular outcome. Thus, for an epigenetic marker, if it is to be relevant to the disease it must have consequences on gene expression. We will not analyse the data for other parameters such as disease-causing mutations.	—

Measure

Time frame

Secondary study parameter is the full transcriptome of the patient material. We will use this data to determine whether the methylation patterns that we find affect gene expression. Biomarkers of necessity reflect disease processes that are correlated to a particular outcome. Thus, for an epigenetic marker, if it is to be relevant to the disease it must have consequences on gene expression. We will not analyse the data for other parameters such as disease-causing mutations.

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Countries

Netherlands

Outcome results