150 research outputs found
Germline genetic variations and survival outcomes of colorectal cancer
BACKGROUND:
Colorectal cancer (CRC) was the second commonest cancer and the third leading
cause of cancer-related deaths worldwide in 2018. In the UK, the overall 5-year
survival rate of CRC patients is approximately 60%. Colorectal cancer patients are
staged based on the staging system recommended by the American Joint Committee
on Cancer (AJCC). The 5-year survival rates vary from approximately 90% for stage
I to 10% for stage IV CRC patients. Although the AJCC stage is the main indicator of
patients’ prognosis, there is still substantial variation in terms of the survival outcomes
of CRC patients within each stage. This merits further examination of other prognostic
factors to improve prediction of CRC survival. Previous evidence revealed that
germline genetic background plays an important role in determining survival
outcomes of CRC patients. However, the human germline genome consists of millions
of genetic variants and no specific genetic loci have been robustly mapped in relation
to prognosis of CRC patients to date. Firstly, this thesis seeks to systematically review
existing literature and explore whether germline genetic variants have been adopted
in published multivariable models in attempts to predict CRC survival. Secondly,
multiple CRC patient cohorts were leveraged to investigate associations between
germline genetic variants and survival outcomes of CRC patients after diagnosis.
METHODS:
A systematic literature search was conducted in MEDLINE and Embase databases to
retrieve published multivariable prediction models that were developed to forecast
survival outcomes of CRC. Risk of bias for included models was assessed using
published evaluation tools and metrics evaluating model performance were extracted
and quantitatively assessed using meta-analysis.
Multiple study cohorts were used in this thesis including the Study of Colorectal
Cancer in Scotland (SOCCS), incident CRC cases from the UK Biobank cohort and
datasets from three previously published clinical trials (QUASAR2, SCOT and
VICTOR). Firstly, germline genetic variants associated with CRC survival that were
reported by published genome-wide association studies (GWAS) were identified by
searching the NHGRI-EBI GWAS catalogue. Associations between these variants
and overall and CRC-specific survival were investigated as a replication study using the SOCCS cohort. Then I explored the potential predictive value of these previously
reported variants in the UK Biobank study by developing a genetic predictor
combining these variants, and evaluated the predictive performance of the predictor
along with other variables (age at diagnosis, sex, AJCC stage and tumour grade)
using the SOCCS as an external validation cohort. The model performance was
assessed in terms of the discriminative ability and model calibration. The next step
was to conduct two candidate genetic association studies to test the potential effects
of two groups of genetic variants—variants associated with CRC risk and variants
associated with prognosis of other cancers—on survival outcomes of CRC patients
from the SOCCS study. These two groups of variants were identified from two large
GWAS meta-analyses and the GWAS catalogue. Stratified analyses were performed
by sex, AJCC stage (stage II/III and IV) and tumour site (colon and rectum). Cox
regression models were used to estimate effects—hazard ratios (HRs)--of genetic
variants on survival outcomes with age at diagnosis, sex and AJCC stage as
covariates. The false discovery rate (FDR) approach was used to correct for multiple
testing. Genetic effects were tested under both the additive and recessive genetic
models.
Finally, I performed a GWAS on both overall and CRC-specific survival by
investigating a total of overall eight million autosomal genetic variants throughout the
genome using the SOCCS study. The effect estimates for each variant were obtained
using a Martingale-residual based approach. Discoveries of the GWAS were then
replicated by performing meta-analysis combining effect estimates from the UK
Biobank cohort and the three clinical trials. Stratified GWASs were also conducted in
SOCCS for stage II/III and stage IV CRC patients separately. Enrichment analyses
were employed to detect potential genomic signals enriched in possible genes and
gene-sets that are involved in relevant biological pathways.
RESULTS:
The systematic literature review identified 83 original prediction models and 52
separate external validation studies. Five models (Basingstoke score, Fong score,
Nordinger score, Peritoneal Surface Disease Severity Score and Valentini nomogram)
were validated in at least two external datasets and showed positive discriminative
ability in terms of model performance. No germline genetic variants had been used
as prognostic predictors in published prediction models. A total of 5,675 CRC patients from the SOCCS cohort, 2,474 incident CRC cases
from the UK Biobank cohort and 4,771 CRC patients from the three clinical trials were
included in the main analysis. By searching the GWAS catalogue, I identified 43
independent genetic variants (r2
<0.2) that were previously linked with CRC survival
outcomes. After correcting for FDR, none of these 43 variants, under the additive
genetic model, were significantly associated with either overall or CRC-specific
survival of CRC patients from the SOCCS cohort. Only three variants (rs17026425,
rs17057166 and rs6854845) at nominal significance (unadjusted p<0.05) showed
concordant direction of effects with previously published GWASs, whereas one
variant with uncorrected p<0.05 showed opposite direction of effect (rs11138220).
The polygenic risk score (PRS) combining the 43 variants was not associated with
CRC survival outcomes. No significant associations after adjusting for FDR were
found in the stratified analysis. Although four variants (rs17280262, rs16867335,
rs6854845 and rs17057166) showed potential effects when the recessive model of
inheritance was used in SOCCS, I failed to replicate these effects using data from the
UK Biobank cohort.
With respect to the predictive performance of the 43 variants in the UK Biobank cohort,
the genetic predictor combining the 43 variants did not show statistically significant C
statistics after internal validation, with the 95% confidence intervals (CIs) including the
null (overall survival: C=0.510, 95%CI=0.498-0.521; CRC-specific survival: C=0.518,
95%CI=0.498-0.530). Similarly, non-significant C statistics were observed for the 43-
variant predictor in the external validation analysis using the SOCCS cohort.
Moreover, the prediction model composed of the 43 variants was poorly calibrated in
both the UK Biobank and the SOCCS cohorts. The model performance remained
nearly unchanged when combining the genetic predictor with other variables including
age at diagnosis, sex, AJCC stage and tumour grade in the SOCCS cohort,
suggesting no incremental predictive value had been introduced by the addition of
genetic variants.
Regarding the other two groups of candidate genetic variants, a total of 128
independent variants (r2<0.2) associated with CRC risk and 82 independent variants
(r2<0.2) associated with survival outcomes of other cancers were included. Overall,
none of the variants were observed in statistically significant associations (after FDR
correction) with CRC survival under the additive model using the SOCCS cohort. The
CRC-risk PRS was not significantly associated with either overall or CRC-specific survival. Stratified analysis did not identify any significant associations after
correcting for FDR. Three CRC-risk variants (rs10161980, rs9537521 and rs7495132)
showed significant genetic effects (recessive model after FDR correction) on survival
outcomes of CRC patients from the SOCCS, and a significant association between
the TT genotype of the variant rs7495132 and CRC-specific survival was also
observed in the UK Biobank cohort (HR=1.69, 95%CI=1.03-2.79, p=0.038).
In relation to the results of the GWAS, I identified one variant in chromosome 6
(rs143664541) that was significantly associated with both overall and CRC-specific
survival (overall survival: HR=1.92, 95%CI=1.52-2.42, p=4.24x10-8; CRC-specific
survival: HR=2.17, 95%CI=1.69-2.78, p=1.14x10-9). Another variant in chromosome
9 (rs75809467) was observed to be significantly associated with CRC-specific
survival (HR=1.80, 95%CI=1.48-2.20, p=7.07x10-9) of patients from the SOCCS study.
However, meta-analysis combining the UK Biobank and the three clinical trials failed
to replicate significant associations between the two GWAS-identified variants and
overall survival of CRC patients. CRC-specific survival was not investigated in the
replication analysis due to lack of available data. In stratified GWASs by AJCC stage,
I identified a variant on chromosome 5 (rs323694) that was significantly associated
with CRC-specific survival of stage II/III patients from the SOCCS cohort (HR=1.33,
95%CI=1.20-1.47, p=2.92x10-8). Genome-wide gene based analysis revealed
significant enrichment of genetic signals in the CCDC135 gene in relation to CRCspecific survival (p=9.92x10-7). For the gene-set based analysis, significant
enrichment of signals was detected in genes involved in the biosynthetic process of
galactolipids for overall survival (p=2.09x10-6) and genes associated with upregulating the differentiation of adipocytes for CRC-specific survival (p=2.52x10-7).
Conclusions
Although the systematic literature review identified no germline genetic variants used
as predictors for CRC survival in published prediction models. Five prediction models
(Basingstoke score, Fong score, Nordinger score, Peritoneal Surface Disease
Severity Score and Valentini nomogram) that include clinic-pathological predictors
can potentially be applied to assist clinical decision-making.
This thesis also presents a comprehensive investigation of potential effects of
germline genetic variants on survival outcomes of CRC patients. For genetic variants
previously linked with CRC survival, the results of the thesis suggest poor reproducibility of these variants given that none of these associations were
successfully replicated in the SOCCS cohort. In addition, the combined effect of the
43 variants, represented by a PRS, on CRC survival is also negligible. There is also
very limited predictive value of these variants as a group in predicting survival
outcomes of CRC. Although small effects cannot be confidently excluded, major
effects of these variants on CRC survival are unlikely.
For genetic variants associated with CRC risk, the lack of association between the
CRC-risk PRS and survival outcomes of CRC indicates that the overall genetic
susceptibility to CRC has no significant subsequent influence on survival outcomes.
For each individual CRC-risk variant, their effects on CRC survival under the additive
genetic model are unlikely to be clinically relevant. However, potential genetic effects
under recessive model were detected for three CRC-risk variants (rs10161980,
rs9537521 and rs7495132) in the SOCCS cohort, especially for the variant rs7495132
whose association with CRC-specific survival was successfully replicated in the UK
Biobank cohort. These findings merit further investigation in future large-scaled
studies. With respect to genetic variants associated with prognosis of other cancers,
the results of this thesis do not support any significant effects of these variants on
survival outcomes of CRC patients, indicating that there is a limited shared genetic
basis across different types of cancers in terms of survival outcomes.
Although the GWAS-identified variant rs143664541 was not successfully replicated in
meta-analysis of results from the UK Biobank and the three clinical trials, effects with
concordant direction were observed across all the datasets on overall survival.
Therefore, future large-scale investigation of this variant in association with CRC
survival outcomes, especially for CRC-specific survival, are warranted. As to the other
GWAS-identified variant rs75809467, further investigation in terms of its effect on
CRC-specific survival is still needed, although no significant association was found
between this variant and overall survival in the replication analysis. A potential variant
rs323694 was identified from the GWAS of stage II/III patients. This variant, if
replicated in the future, could be of clinical relevance in stratifying stage II/III CRC
patients of varied prognostic profiles so as to assist informing tailored treatment
strategies. The results of gene and gene-set based analysis provide preliminary
evidence favouring future exploration of the biological roles of the CCDC135 gene
and pathways associated with the biosynthetic process of galactolipids and the
differentiation of adipocytes in CRC progression
Institutional investors and hedge fund activism
This thesis studies the institutional investor background in order to understand the working of hedge fund activism: how institutional investors affect hedge fund activists target selection and how activists share information and build alliances through social connections to achieve their goals.
Chapter 2 utilizes a rich literature on institutional investors' governance roles and develops simple measures of institutional discontent expressed through holding, trading and voice channels, to predict hedge fund activism target selection. Discontent expressed through all three channels leads to subsequent targeting. Medium sized dissatisfied owners and sellers seem to be the main driving force, and institutions' discretionary disagreements on management compensation and governance related proposals have the highest explanatory power among other voice channels. Activists are more likely to gain higher announcement returns and threaten to take hostile actions against management with more discontented institutional investors in the target companies. Discontented institutions are more likely to vote pro-activist in the subsequent annual meetings after campaigns.
Chapter 3 uses a social network framework to study information dissemination during activist campaigns. Actively managed funds whose managers are socially connected to the lead activist are more likely to increase their ownership in the target firms around the activist disclosure. In the cross sectional analysis, we find that the effect is stronger if the activists have better track records and if the ties are established via club membership, charity works, and other small circles. Connected institutions also earn significantly higher announcement returns relative to non-connected funds. The presence of connected institutions contributes to the activist's campaign success. Additional tests are performed to rule out alternative explanations such as fund manager ability or similarity in portfolio choices.
Chapter 4 goes one step further to study alliance building among activist investors and institutional investors during the campaign period. A socially connected institution is 1.1 percentage points more likely to increase its ownership in the target firm during the campaign period, compared to funds that are not socially connected to the activist. We use a subsample that includes all institutions subject to M&As before activism events to identify plausibly exogenous shocks to social connections and find similar results. Furthermore, connected institutions also perform significantly better on their investments than non-connected institutions and they are more likely to vote pro-activist in routine proposals, especially director election proposals. The effect is stronger if connected institutions also purchase target stocks during a campaign.
The thesis contributes to the literature by developing measures of revealed institutional governance preference based on theoretical and survey evidence in the literature. It also uncovers a channel through which hedge fund activists share information and build alliances and push for corporate changes facilitated by mutual benefits amongst their fellow institutional allies
Visual Investigation on Effect of Structural Parameters and Operation Condition of Two-phase Ejector
As an important component in transcritical CO2 refrigeration cycle, complex flow in ejector have not been clearly elucidated. In this paper, CO2 flow in two-phase rectangle ejector was investigated experimentally by visualization measurement. The phase transition and the relaxation phenomena in the ejector were observed. By analyze the picture and the data collected from this experiment, we study the relationship between efficiency of ejector and the phase transition position in the ejector. Firstly, the microstructure of the flow pattern in the ejector was captured by a high speed digital video camera with a microscope to analyze the mixing process in mixing chamber. It was found that there were two stages with different characteristics in mixing process ,which were named fluid mixing section and fluid equilibrium section. When fluid get through mixing channel, the ejector realize the majority functions of entrainment in the first stage, and the ejector also homogenize the velocity of primary fluid and secondary flow by the way of flow core expand to almost all the channel in the second stage. Secondly, based on the comparison of pictures collected from different ejectors under different operating conditions, we found that phase transition position and the form of phase transition was mainly depended on the entrance condition of motive nozzle. For an ejector that keeps the suction nozzle under the same operation condition, when the phase transition point trend to exit of motive nozzle, in mixing channel ,motive flow will occupy more space meanwhile the relaxation phenomena occurred in longer region. It was worth mentioning that the phase transition point will change with different operation condition. But there exist only one best position where the ejector contributes to best efficiency. So, it is of great significance to treat phase transition point as an important sign which was easy to be recognized. Visualization research of ejector will be an important reference for theoretical study of flow pattern in the ejector. It also can provide some date to validate the results from the numerical calculation. The visualization study of ejector will also be the basis of further learn of shock waves and delayed phase transition in the ejector
Federated Deep Multi-View Clustering with Global Self-Supervision
Federated multi-view clustering has the potential to learn a global
clustering model from data distributed across multiple devices. In this
setting, label information is unknown and data privacy must be preserved,
leading to two major challenges. First, views on different clients often have
feature heterogeneity, and mining their complementary cluster information is
not trivial. Second, the storage and usage of data from multiple clients in a
distributed environment can lead to incompleteness of multi-view data. To
address these challenges, we propose a novel federated deep multi-view
clustering method that can mine complementary cluster structures from multiple
clients, while dealing with data incompleteness and privacy concerns.
Specifically, in the server environment, we propose sample alignment and data
extension techniques to explore the complementary cluster structures of
multiple views. The server then distributes global prototypes and global
pseudo-labels to each client as global self-supervised information. In the
client environment, multiple clients use the global self-supervised information
and deep autoencoders to learn view-specific cluster assignments and embedded
features, which are then uploaded to the server for refining the global
self-supervised information. Finally, the results of our extensive experiments
demonstrate that our proposed method exhibits superior performance in
addressing the challenges of incomplete multi-view data in distributed
environments
The Global and Regional Prevalence of Abdominal Aortic Aneurysms:A Systematic Review and Modelling Analysis
Objective:
To estimate the global and regional prevalence and cases of abdominal aortic aneurysms (AAA) in 2019 and to evaluate major associated factors.
Summary Background Data:
Understanding the global prevalence of AAA is essential for optimizing health services and reducing mortality from reputed AAA.
Methods:
PubMed, MEDLINE and Embase were searched for articles published until Oct 11 2021. Population-based studies that reported AAA prevalence in the general population, defined AAA as an aortic diameter of 30mm or greater with ultrasonography or computed tomography. A multilevel mixed-effects meta-regression approach was used to establish the relation between age and AAA prevalence for high- socio-demographic index (H-SDI) and low-and middle-SDI (LM-SDI) countries. Odds ratios (ORs) of AAA associated factors were pooled using a random-effects method.
Results:
We retained 54 articles across 19 countries. The global prevalence of AAA among persons aged 30-79 years was 0.92% (95% confidence interval, CI: 0.65-1.30), translating to a total of 35.12 million (95% CI: 24.94-49.80) AAA cases in 2019. Smoking, male sex, family history of AAA, advanced age, hypertension, hypercholesterolemia, obesity, cardiovascular disease, cerebrovascular disease, claudication, peripheral artery disease, pulmonary disease and renal disease were associated with AAA. In 2019, the Western Pacific region (WPR) had the highest AAA prevalence at 1.31% (95% CI: 0.94-1.85), while the African region (AFR) had the lowest prevalence at 0.33% (95% CI: 0.23-0.48).
Conclusions:
A substantial proportion of people are affected by AAA. There is a need to optimise epidemiological studies to promptly respond to at-risk and identified cases to improve outcomes
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