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تحليل ماكات لكتاب فريدريك نيتشه : ما وراء الخير والشر : تباشير فلسفة المستقبل
هذا الكتاب وهو كتاب مركزي بين مؤلفات نيتشه، يأتي بعد هكذا تكلم زرادشت، وينتمي إلى المرحلة الختامية من سيرة نيتشه الفكرية، ويشكل حقل اختبار للأفكار الدينامية التي تميز بها نيتشه من سواه من الفلاسفة : من إرادة القدرة إلى العود الأبدي والفوق-إنساني، مرورا بتخطي الثنائية الميتافيزيقية في وهم الذات وحرية الإرادة وتناقض القيم. ونكرر القول بأن أهمية هذا الكتاب تكمن لا في ما يقول ويثبت، بل في كيف يقول ويثبت. أهمية نيتشه تكمن بالأحرى في منهجه النسابي (الجينايولوجيا) في كونه إذ يظهر تعدد المعاني المفترضة واحدة في الأفهوم، يهدم المنطق القائم على مبدأ الهوية من أساسه. ويفتح الباب، إذ يعاند الستمة، واسعا على اللامتناهي. ويوقظ \"الروح الفلسفي\" من \"سباته الدغمائي\" فيغدو شرطا لا بد منه من شروط إمكان القول الفلسفي وتجدده في طول القرن العشرين وعرضه.
Book
A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC
Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with
APC
playing a central role in predicting overall survival.
APC
may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any
APC
mutation carry a worse prognosis than single
APC
mutation tumours; however, two
APC
mutation tumours with mutant
KRAS
and
TP53
confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for
APC
and suggests that sequencing of
APC
may have clinical utility in the routine staging and potential therapeutic assignment for CRC.
APC
is a well-known tumour suppressor that is frequently inactivated in colorectal cancer. Here, the authors sequence more than 1000 cancer genes in 468 colorectal cancers and show that mutation signatures can be used to classify the tumours and that multiple mutations in
APC
are associated with a poor prognosis.
Journal Article
A general framework for functionally informed set-based analysis: Application to a large-scale colorectal cancer study
Genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with various phenotypes, but together they explain only a fraction of heritability, suggesting many variants have yet to be discovered. Recently it has been recognized that incorporating functional information of genetic variants can improve power for identifying novel loci. For example, S-PrediXcan and TWAS tested the association of predicted gene expression with phenotypes based on GWAS summary statistics by leveraging the information on genetic regulation of gene expression and found many novel loci. However, as genetic variants may have effects on more than one gene and through different mechanisms, these methods likely only capture part of the total effects of these variants. In this paper, we propose a summary statistics-based mixed effects score test (sMiST) that tests for the total effect of both the effect of the mediator by imputing genetically predicted gene expression, like S-PrediXcan and TWAS, and the direct effects of individual variants. It allows for multiple functional annotations and multiple genetically predicted mediators. It can also perform conditional association analysis while adjusting for other genetic variants (e.g., known loci for the phenotype). Extensive simulation and real data analyses demonstrate that sMiST yields p-values that agree well with those obtained from individual level data but with substantively improved computational speed. Importantly, a broad application of sMiST to GWAS is possible, as only summary statistics of genetic variant associations are required. We apply sMiST to a large-scale GWAS of colorectal cancer using summary statistics from ∼120, 000 study participants and gene expression data from the Genotype-Tissue Expression (GTEx) project. We identify several novel and secondary independent genetic loci.
Journal Article
Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study
Background
Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.
Results
We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (
P
< 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (
P
< 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.
Conclusions
Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.
Journal Article
Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
Background
Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population.
Results
We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum
n
= 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (
p
< 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (
HFE
,
KIT
,
HBS1L/MYB
,
CITED2/FILNC1
,
ABO
,
HBA1/2
, and
PLIN4/5
). For example, the
HBA1/2
locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP.
Conclusion
This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the
HBA1/2
locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.
Journal Article
Strategies for Enriching Variant Coverage in Candidate Disease Loci on a Multiethnic Genotyping Array
Investigating genetic architecture of complex traits in ancestrally diverse populations is imperative to understand the etiology of disease. However, the current paucity of genetic research in people of African and Latin American ancestry, Hispanic and indigenous peoples in the United States is likely to exacerbate existing health disparities for many common diseases. The Population Architecture using Genomics and Epidemiology, Phase II (PAGE II), Study was initiated in 2013 by the National Human Genome Research Institute to expand our understanding of complex trait loci in ethnically diverse and well characterized study populations. To meet this goal, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially improve fine-mapping and functional discovery by increasing variant coverage across multiple ethnicities at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits. Studying the frequency distribution of clinically relevant mutations, putative risk alleles, and known functional variants across multiple populations will provide important insight into the genetic architecture of complex diseases and facilitate the discovery of novel, sometimes population-specific, disease associations. DNA samples from 51,650 self-identified African ancestry (17,328), Hispanic/Latino (22,379), Asian/Pacific Islander (8,640), and American Indian (653) and an additional 2,650 participants of either South Asian or European ancestry, and other reference panels have been genotyped on MEGA by PAGE II. MEGA was designed as a new resource for studying ancestrally diverse populations. Here, we describe the methodology for selecting trait-specific content for use in multi-ethnic populations and how enriching MEGA for this content may contribute to deeper biological understanding of the genetic etiology of complex disease.
Journal Article
CD163 Immunohistochemistry Is Superior to CD68 in Predicting Outcome in Classical Hodgkin Lymphoma
In recent years, research has increasingly focused on the microenvironment of classical Hodgkin lymphoma (CHL) as a predictor of treatment outcome. The focus of this study was to assess the interobserver reproducibility in interpreting macrophage-associated immunohistochemistry (IHC) for CD68 and CD163 in a retrospective cohort of 88 patients with CHL.
Staining results were correlated with clinical outcome in all patients and those with a high international prognostic score (IPS).
The intraclass correlation (ICC) for the five hematopathologists interpreting the IHC was stronger for CD163 (0.70) than for CD68 (0.50). Using a cutoff of 25% mean macrophage reactivity and including all patients, a statistically significant difference in overall survival (OS) was seen only for CD163 (P = .0006) and not for CD68 (P = .414). Patients with a mean CD163 reactivity of 25% or more had a median OS of 71 months vs 101 months for patients with less than 25% reactivity. CD163 retained statistical significance in multivariate analysis. In patients with advanced-stage CHL with high IPS, OS was also significantly worse for those with a mean CD163 reactivity of 25% or higher.
Our study confirms previous reports of a prognostic role of tumor-infiltrating macrophages in CHL, but only for CD163. Although most of the literature supports an increasing role of macrophage IHC as a predictor of clinical outcome, successful clinical translation will require a standardized method and reporting system.
Journal Article
Moving from one to many: insights from the growing list of pleiotropic cancer risk genes
Summary
Pleiotropy, a phenomenon in which a single gene affects multiple phenotypes, is becoming very common among different cancer types and cancer-related phenotypes, such as those in hormonal, cardiometabolic and inflammatory/immune conditions. The discovery of pleiotropic associations can improve our understanding of cancer and help to target investigation of genes with greater clinical relevance.
Journal Article
Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study
Aims/hypothesisType 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.MethodsWe conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.ResultsFour novel associations were identified (p < 5 × 10−9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.Conclusions/interpretationOur findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.Data availabilityFull summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics).
Journal Article