Explore the vast range of titles available.

Background The interactions of multiple single nucleotide polymorphisms (SNPs) are highly hypothesized to affect an individual's susceptibility to complex diseases. Although many works have been done to identify and quantify the importance of multi-SNP interactions, few of them could handle the genome wide data due to the combinatorial explosive search space and the difficulty to statistically evaluate the high-order interactions given limited samples. Results Three comparative experiments are designed to evaluate the performance of MegaSNPHunter. The first experiment uses synthetic data generated on the basis of epistasis models. The second one uses a genome wide study on Parkinson disease (data acquired by using Illumina HumanHap300 SNP chips). The third one chooses the rheumatoid arthritis study from Wellcome Trust Case Control Consortium (WTCCC) using Affymetrix GeneChip 500K Mapping Array Set. MegaSNPHunter outperforms the best solution in this area and reports many potential interactions for the two real studies. Conclusion The experimental results on both synthetic data and two real data sets demonstrate that our proposed approach outperforms the best solution that is currently available in handling large-scale SNP data both in terms of speed and in terms of detection of potential interactions that were not identified before. To our knowledge, MegaSNPHunter is the first approach that is capable of identifying the disease-associated SNP interactions from WTCCC studies and is promising for practical disease prognosis.

Health-related quality of life (HRQoL) is a significant prognostic factor for overall survival in hepatocellular carcinoma (HCC) patients, and this is independent of stage and liver function. Inflammation plays a significant role in HCC development and progression. It was hypothesized that the inflammatory status of HCC patients may affect their HRQoL. The relationship between HRQoL and inflammatory status was explored using indicators IL-8 level and modified inflammation-based index (mIBI, based on IL-8, C-reactive protein, and albumin). From 2007-2011, HCC patients were enrolled prospectively. Baseline HRQoL assessment utilized the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and QLQ-HCC18; clinical and laboratory data were collected at diagnosis. Two summary indices, C30 and HCC18 index-scores, were calculated. Correlation analyses were performed between HRQoL and inflammatory markers. In the 445 patients studied, significant correlations were found between IL-8 levels and EORTC QLQ-C30, QLQ-HCC18, C30, and HCC18 index-scores. The strongest correlated factors were those reflective of constitutional symptoms, namely QLQ-C30 \"appetite loss\" (with Pearson's correlation coefficient, =0.322, <0.0001); QLQ-C30 \"fatigue\" ( =0.311, <0.0001); QLQ-C30 \"role functioning\" ( =-0.305, <0.0001); QLQ-HCC18 \"nutrition\" ( =0.317, <0.0001); and QLQ-HCC18 \"fatigue\" ( =0.306, <0.0001). In addition, moderate but significant correlations were also observed with HCC18 index score ( =0.321, <0.0001), and C30 index score ( =0.306, <0.0001). HRQoL factors were also significantly correlated with mIBI. Baseline HRQoL using the conventional assessments of EORTC QLQ-C30 and QLQ-HCC18, as well as C30 and HCC18 index-scores, significantly correlated with inflammatory indicators (IL-8 level and mIBI) in HCC patients. Among the strongest correlations were those between IL-8 level and the two index-scores, as well as HRQoL aspects that represent constitutional symptoms. When paralleled with molecular findings, traditional HRQoL assessment in HCC has gained a new level of understanding: pattern recognition within an HRQoL instrument could potentially identify patients with more severe inflammatory state.

Objective: In this study, we set out to investigate the relationship between angiotensin-converting enzyme (ACE) I/D polymorphism, serum ACE activity and bone mineral density (BMD) in older Chinese. Methods: A standardized, structured, face-to-face interview was performed to collect demographic information. BMD was measured using dual-energy X-ray absorptiometry (DXA). I/D genotypes of ACE were determined by polymerase chain reaction (PCR) amplification. Serum ACE activity was determined photometrically by a commercially available kinetic kit. Multiple linear regression analysis was used to examine the relationship between ACE I/D polymorphism, serum ACE activity and BMD. Results: A total of 1567 males and 1760 females were selected for analyzing the relationship between ACE I/D polymorphism and BMD. There was no significant difference in spine BMD, total hip BMD and femur neck BMD among different ACE I/D genotypes both in males and females. A total of 1699 males and 1739 females were selected for analyzing the relationship between serum ACE activity and BMD. There was also no significant difference in spine BMD, total hip BMD and femur neck BMD among different serum ACE activity groups both in males and females. Conclusion: There was no relationship between ACE I/D polymorphism, serum ACE activity and BMD in older Chinese.

Background Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip .

Fernando Rivadeneira and colleagues in the Genetic Factors for Osteoporosis Consortium report a large-scale meta-analysis identifying new loci associated with bone mineral density (BMD) and risk of fracture. Thirty-two new loci are found to be associated with BMD, and 6 loci confer higher risk for low-trauma bone fracture. Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance ( P < 5 × 10 −8 ). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk ( P < 5 × 10 −4 , Bonferroni corrected), of which six reached P < 5 × 10 −8 , including at 18p11.21 ( FAM210A ), 7q21.3 ( SLC25A13 ), 11q13.2 ( LRP5) , 4q22.1 ( MEPE ), 2p16.2 ( SPTBN1 ) and 10q21.1 ( DKK1 ). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

Bone mineral density (BMD) is a measure of osteoporosis and is useful in evaluating the risk of fracture. In a genome-wide association study of BMD among 20,100 Icelanders, with follow-up in 10,091 subjects of European and East-Asian descent, we found a new BMD locus that harbours the PTCH1 gene, represented by rs28377268 (freq. 11.4–22.6%) that associates with reduced spine BMD ( P =1.0 × 10 −11 , β =−0.09). We also identified a new spine BMD signal in RSPO3 , rs577721086 (freq. 6.8%), that associates with increased spine BMD ( P =6.6 × 10 −10 , β =0.14). Importantly, both variants associate with osteoporotic fractures and affect expression of the PTCH1 and RSPO3 genes that is in line with their influence on BMD and known biological function of these genes. Additional new BMD signals were also found at the AXIN1 and SOST loci and a new lead SNP at the EN1 locus. Bone mineral density (BMD) is the best predictor of osteoporotic fracture risk. Here, the authors perform a genome wide association study in Icelanders and people of European and East-Asian descent, and identify a new allele in intron 15 of the PTCH1 gene that associates with reduced BMD.

Purpose Both Inflammation and health-related quality of life (HRQoL) are independent prognosticators in HCC patients. We hypothesized that inflammation can cause impairment in HRQoL and investigated the correlation between inflammatory status and HRQoL in HCC patients. Methods Clinical, laboratory and HRQoL (using EORTC QLQ-C30, QLQ-HCC18, C30 and HCC18 index-scores) data were prospectively collected from HCC patients at diagnosis. Correlation analyses were performed between HRQoL and inflammation-based markers including C-reactive protein (CRP), CRP/albumin ratio (CRP/alb), Glasgow Prognostic Score (GPS), Inflammation-Based Index (IBI) and Prognostic Index (PI). Results Among 445 HCC patients, higher inflammatory states were significantly correlated with worse HRQoL. For CRP and CRP/alb ratio, the HRQoL factors with higher correlations included C30 and HCC18 index-scores, certain QLQ-C30 domains and items (‘physical functioning’, ‘role functioning’, ‘fatigue’, ‘pain’, ‘appetite loss’) and QLQ-HCC18 items (‘fatigue’, ‘body image’, ‘nutrition’ and ‘abdominal swelling’), where the Pearson’s correlation coefficients were up to 0.416. Multivariate analyses indicated that worse HRQoL factors were significantly correlated with worse scores in GPS, IBI and PI. Conclusion In HCC patients, inflammatory status correlates with HRQoL at presentation. In particular, relatively stronger correlations with CRP-based markers have been observed in HRQoL scales that assess constitutional symptoms (QLQ-C30 ‘physical functioning’, ‘role functioning’, ‘fatigue’, ‘appetite loss’ and QLQ-HCC18 ‘fatigue’ and ‘nutrition’) and tumor burden (QLQ-C30 ‘pain’ and QLQ-HCC18 ‘abdominal swelling’ and ‘body image’). Future studies are warranted to evaluate whether intervention that reduces inflammation could improve HRQoL in HCC patients.

Research into the mechanisms of human adaptation to the hypoxic environment of high altitude is of great interest to the fields of human physiology and clinical medicine. Recently, the gene EGLN1, from the hypoxia-inducible factor (HIF) pathway, was identified as being involved in the hypoxic adaptation of highland Andeans and Tibetans. Both highland Andeans and Tibetans have adapted to an extremely hypoxic habitat and less attention has been paid to populations living in normoxic conditions at sea level and mild-hypoxic environments of moderate altitude, thus, whether a common adaptive mechanism exists in response to quantitative variations of environmental oxygen pressure over a wide range of residing altitudes is unknown. Here, we first performed a genome-wide association study of 35 populations from the Human Genome Diversity-CEPH Panel who dwell at sea level to moderate altitude in Eurasia (N = 691; 0–2,500 m) to identify the genetic adaptation profile of normoxic and mild-hypoxic inhabitants. In addition, we systematically compared the results from the present study to six previously published genome-wide scans of highland Andeans and Tibetans to identify shared adaptive signals in response to quantitative variations of oxygen pressure. For normoxic and mild-hypoxic populations, the strongest adaptive signal came from the mu opioid receptor-encoding gene (OPRM1, 2.54 × 10−9), which has been implicated in the stimulation of respiration, while in the systematic survey the EGLN1-DISC1 locus was identified in all studies. A replication study performed with highland Tibetans (N = 733) and sea level Han Chinese (N = 748) confirmed the association between altitude and SNP allele frequencies in OPRM1 (in Tibetans only, P < 0.01) and in EGLN1-DISC1 (in Tibetans and Han Chinese, P < 0.01). Taken together, identification of the OPRM1 gene suggests that cardiopulmonary adaptation mechanisms are important and should be a focus in future studies of hypoxia adaptation. Furthermore, the identification of the EGLN1 gene from the HIF pathway suggests a common adaptive mechanism for Eurasian human populations residing at different altitudes with different oxygen pressures.

ObjectivesThis is a prospective study evaluating NEPA in patients with breast cancer (the NEPA group), who received (neo)adjuvant AC chemotherapy (consisting of doxorubicin 60 mg/m2 and cyclophosphamide 600 mg/m2). The primary objectives were to assess the efficacy and safety of NEPA in controlling chemotherapy-induced nausea and vomiting (CINV). The secondary objectives were to compare CINV between the NEPA group and historical controls (the APR group) who received aprepitant in an earlier prospective randomised study.Patients and methods60 patients participated in the NEPA group; 62 were in the APR group. Eligibility criteria of both groups were similar, that is, Chinese patients with breast cancer who were treated with (neo)adjuvant AC. NEPA group received NEPA and dexamethasone; APR group received aprepitant, ondansetron and dexamethasone. Individuals filled in self-reported diary, visual analogue scale for nausea and Functional Living Index-Emesis questionnaire.ResultsWithin the NEPA group, 70.0%, 85.7% and 60.0%, respectively reported complete response in the acute, delayed and overall phases in cycle 1 AC. When compared with the historical APR group during cycle 1 AC, NEPA group achieved significantly higher rates of complete response, complete protection, total control, ‘no significant nausea’ and ‘no nausea’ in the delayed phase; similar findings were noted in the overall phase with significantly better quality of life. Superior efficacy of NEPA was maintained over multiple cycles. Both antiemetic regimens were well tolerated.ConclusionIn this study on Chinese patients with breast cancer who were uniformly receiving AC, NEPA was effective in controlling CINV.Trial registration number NCT03386617.

Background: Alzheimer's disease (AD) is a neurodegenerative disease with a higher prevalence in women. Expression of estrogen receptor 1 (ESR1) gene has been identified throughout the brain. Owing to the putative neuroprotective effects of estrogen, estrogen receptor gene is a potential candidate modulating the development of AD. Preliminary associations between two polymorphisms of ESR1 (PvuII and XbaI) gene and AD have been reported. Methods: In this study, 16 single nucleotide polymorphisms (SNPs) of the ESR1 gene (including four commonly studied ESR1 SNPs and 12 other tagging SNPs selected from the HapMap database) were investigated to further evaluate the association between ESR1 polymorphisms and the risk of AD in the Chinese population. Results: A total of 233 Chinese AD patients and 245 age-matched elderly control subjects were recruited. Genetic associations were analyzed by chi-square test and interaction effect was analysed by logistic regression analysis. Five SNPs (clustered between intron 3 and intron 7) were associated with the risk of AD (p-value ranges from 0.001 to 0.035); another two SNPs (located on exon 2 and intron 2) were shown to modulate the age-at-onset (AAO) in AD (p-value = 0.036 and 0.011). Conclusions: ESR1 gene polymorphisms may be associated with the AAO in AD. The present results provided information for possible associations between certain polymorphisms of ESR1 gene and the risk of AD.