1.Identification of a novel aberrant spliceosome of MPL gene (MPLL391-V392ins12)in patients with myeloproliferative neoplasms.
Ruiyuan TIAN ; Xiuhua CHEN ; Jianmei CHANG ; Na ZHANG ; Yanhong TAN ; Zhifang XU ; Fanggang REN ; Junxia ZHAO ; Jie PAN ; Haixiu GUO ; Xiaojuan WANG ; Hongwei WANG
Chinese Journal of Hematology 2015;36(7):559-562
OBJECTIVETo identify the MPL L391-V392ins12 spliceosome and analyze its frequencies in patients with myeloproliferative neoplasms (MPN).
METHODSMPL aberrant spliceosome was identified through reverse transcription polymerase chain reaction (RT-PCR)combined with cloning sequencing. The mutation of this spliceosome in 248 MPN patients and 200 normal people was determined by allele-specific polymerase chain reaction (AS-PCR).
RESULTSA novel aberrant spliceosome of MPL gene (MPL L391-V392ins12)was identified, i.e. 36 bp intron was retained between exon7 and exon8, and there were 12 amino acids (EGLKLLPADIPV)inserted. MPL L391-V392ins12 mutation was detected in 19 (7.66%)of the 248 patients with MPN, including 1 (1.92%) of 52 patients with PV, 14 (9.66%) of 145 with ET, and 4 (7.84%) of 51 with PMF. And the mutation was not detected in the group of 200 normal people.
CONCLUSIONMPL L391-V392ins12 spliceosome is an aberrant spliceosome present in the MPN. It can be detected in PV, ET and PMF, and more frequently in ET and PMF. This mutation may play an important role in the process of MPN.
Humans ; Mutation ; Myeloproliferative Disorders ; genetics ; Neoplasms ; genetics ; Polymerase Chain Reaction ; Receptors, Thrombopoietin ; genetics ; Spliceosomes
2.Ambient PM2.5 during pregnancy and risk on preterm birth.
Yanpeng CHENG ; Yongliang FENG ; Xiaoli DUAN ; Nan ZHAO ; Jun WANG ; Chunxia LI ; Pengge GUO ; Bingjie XIE ; Fang ZHANG ; Haixiu WEN ; Mei LI ; Ying WANG ; Suping WANG ; Yawei ZHANG
Chinese Journal of Epidemiology 2016;37(4):572-577
OBJECTIVETo investigate the association between ambient fine particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) and the risk on preterm birth.
METHODSA total of 1 882 pregnant women with local residency of Taiyuan city and underwent delivery at the First Hospital of Shanxi Medical University with the dates of conception between January 1 and December 31, 2013, were enrolled in the study. Information on general demographics, home address and history on pregnancy, lifestyle and related environmental factors were collected through in-person interview. Birth outcomes and maternal complications were abstracted from medical records. Data on the amount of daily average PM2.5 from 8 monitor points in Taiyuan city, between March 1, 2012 and December 31, 2013 were also collected. Individual exposure during pregnancy were calculated using the inverse-distance weighting method, based on home address. Multivariate unconditional logistic regression model was used to examine the associations among PM2.5 exposure, risk of preterm birth and related clinical subtypes.
RESULTSThe overall incidence of preterm birth was 8.21% (151/1 839)in 1 839 pregnant women. Exposure to ambient PM2.5 during the second week prior to delivery was associated with an increased risk of preterm birth (OR=1.087, 95% CI: 1.001-1.182 per 10 μg/m(3) increase) and mild preterm birth (OR=1.099, 95% CI: 1.007-1.200 per 10 μg/m(3)). Compared to data from the China Environmental Air Quality Standard, higher level of exposure (≥75 μg/m(3)) of PM2.5 during the second week before delivery was associated with an increased risk of preterm birth (OR=1.008, 95%CI: 1.000-1.017) but the association was mainly seen for mild preterm birth (OR=1.010, 95%CI: 1.001-1.018).
CONCLUSIONSRESULTS from our study showed that exposure to high level of PM2.5 during late pregnancy would increase the risk of preterm birth. Future large studies are needed to examine the association by preterm clinical subtypes and to elucidate potential underlying mechanisms.
China ; epidemiology ; Environmental Exposure ; adverse effects ; analysis ; Female ; Humans ; Incidence ; Infant, Newborn ; Logistic Models ; Maternal Exposure ; Particle Size ; Particulate Matter ; analysis ; toxicity ; Pregnancy ; Pregnancy Complications ; Premature Birth ; chemically induced ; epidemiology ; Public Health ; statistics & numerical data