m+Medelevator.RU
← Поиск публикаций
Proteomics · 2015

Network-based proteomic analysis for postmenopausal osteoporosis in Caucasian females.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Zhang Lan, Liu Yao-Zhong, Zeng Yong, Zhu Wei, Zhao Ying-Chun, Zhang Ji-Gang, Zhu Jia-Qiang, He Hao, Shen Hui, Tian Qing, Deng Fei-Yan, Papasian Christopher J, Deng Hong-Wen

Аннотация

Menopause is one of the crucial physiological events during the life of a woman. Transition of menopause status is accompanied by increased risks of various health problems such as osteoporosis. Peripheral blood monocytes can differentiate into osteoclasts and produce cytokines important for osteoclast activity. With quantitative proteomics LC-nano-ESI-MS(E) (where MS(E) is elevated-energy MS), we performed protein expression profiling of peripheral blood monocytes in 42 postmenopausal women with discordant bone mineral density (BMD) levels. Traditional comparative analysis showed proteins encoded by four genes (LOC654188, PPIA, TAGLN2, YWHAB) and three genes (LMNB1, ANXA2P2, ANXA2) were significantly down- and upregulated, respectively, in extremely low- versus high-BMD subjects. To study functionally orchestrating groups of detected proteins in the form of networks, we performed weighted gene coexpression network analysis and gene set enrichment analysis. Weighted gene coexpression network analysis showed that the module including the annexin gene family was most significantly correlated with low BMD, and the lipid-binding related GO terms were enriched in this identified module. Gene set enrichment analysis revealed that two significantly enriched gene sets may be involved in postmenopausal BMD variation by regulating pro-inflammatory cytokines activities. To gain more insights into the proteomics data generated, we performed integrative analyses of the datasets available to us at the genome (DNA level), transcriptome (RNA level), and proteome levels jointly.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты