تالیفات

 

Interleukin-1 gene cluster and IL-1 receptor polymorphisms in Iranian patients with systemic lupus erythematosus

Authers: Zahra Tahmasebi • Mahmoud Akbarian • Sedigheh Mirkazemi • Abtin Shahlaee • Zahra Alizadeh • Ali Akbar Amirzargar • Ahmad Reza Jamshidi • Shima Ghoroghi • Shiva Poursani • Keramat Nourijelyani • Mahdi Mahmoudi

Abstract: Systemic lupus erythematosus (SLE) is a systemic autoimmune disease of unknown etiology with a complex pathogenesis involving multiple genetic and environmental contributions. Single-nucleotide polymorphisms (SNPs) in cytokine genes are associated with higher or lower cytokine activity, which can alter the susceptibility to certain diseases or their clinical outcomes. We investigated SNPs of the IL-1 family in Iranian SLE patients and normal individuals. We obtained blood samples from 207 SLE patients and 213 healthy controls. Cytokine genotyping was performed by polymerase ... سال انتشار: 2013
 

Effect of HLA-B*27 and its Subtypes on Clinical Manifestations and Severity of Ankylosing Spondylitis in Iranian Patients

Authers: Sasan Fallahi1, 2, Mahdi Mahmoudi2, Mohammad Hossein Nicknam3, 5, Farhad Gharibdoost2, Elham Farhadi4, Azad Saei5, Keramat Nourijelyani6, Nooshin Ahmadzadeh2, and Ahmad Reza Jamshidi2

Abstract: The aim of this study was to assess the role of HLA-B*27 and it’s subtypes in determining severity and clinical manifestations of ankylosing spondylitis (AS). A total of 163 AS patients were assessed for clinical manifestations and severity using structured questionnaires. HLA-B*27 screening and B*27 sub-typing were performed by PCR. One hundred twenty two patients (74.8%) were B*27 positive. The male to female ratio, peripheral arthritis, steroid use, intense dorsal kyphosis and ... سال انتشار: 2013
 

Random Forests Analysis: A modern statistical method for screening in high-dimensional studies and its application in a population-based genetic association study

Authers: Sahar Noori1, Keramat Nourijelyani 2*, Kazem Mohammad3, Mohammad Hossein Niknam4, Mahdi Mahmoudi5, Laris Andonian6, and Arash Akaberi7

Abstract: Technology advances in this century, especially, in molecular generics yields high volume, high dimensional data. This creates many unprecedented challenges for statisticians who are responsible for analysis of such data. Although logistic regression method is quite popular in association analysis in medical researches but it has some serious limitations in handling high dimensional data. In present study, our goal is introduce a modern model-free statistical method called random forest that we believe is able to overcome difficulties ... سال انتشار: 2012
 

Association between Endoplasmic Reticulum Aminopeptidase-1 (ERAP-1) and Susceptibility to Ankylosing Spondylitis in Iran

Authers: Mahdi Mahmoudi1, 2, 3, Ahmad Reza Jamshidi2, Ali Akbar Amirzargar1, 3, Elham Farhadi1, Keramat Nourijelyani4, Sasan Fallahi2, 5, Mona Oraei3, Sahar Noori4, and Mohammad Hossein Nicknam1, 3

Abstract: Ankylosing Spondylitis (AS) is an inflammatory arthritis, which affects mainly spine and sacroiliac joints. According to recent studies, ERAP1 is the second most common candidate gene for AS susceptibility after HLA-B27. The aim of this study was to determine the association of ERAP1 gene polymorphisms with AS in Iranian population. The study group comprised 387 Iranian AS patients and 316 healthy controls from Iran. Using Real Time PCR allelic discrimination method, we genotyped four SNPs ... سال انتشار: 2012
 

Random Forests Analysis: A modern statistical method for screening in high-dimensional studies and its application in a population-based genetic association study

Authers: Sahar Noori, Keramat Nourijelyani, Kazem Mohammad, Mohammad Hossein Niknam, Mahdi Mahmoudi, Laris Andonian, Arash Akaberi

Abstract: Technology advances in this century, especially, in molecular generics yields high volume, high dimensional data. This creates many unprecedented challenges for statisticians who are responsible for analysis of such data. Although logistic regression method is quite popular in association analysis in medical researches but it has some serious limitations in handling high dimensional data. In present study, our goal is introduce a modern model-free statistical method called random forest that we believe is able to overcome difficulties ... سال انتشار: 2011