scholarly journals Germline Genetic Factors Influence Outcome of Interferon Alpha Therapy in Polycythemia Vera

Blood ◽  
2020 ◽  
Author(s):  
Roland Jäger ◽  
Heinz Gisslinger ◽  
Elisabeth Fuchs ◽  
Edith Bogner ◽  
Jelena D. Milosevic Feenstra ◽  
...  
Keyword(s):  
Polycythemia Vera ◽  
Interferon Alpha ◽  
Genetic Factors ◽  
Myeloproliferative Neoplasms ◽  
Association Studies ◽  
Study Cohort ◽  
Molecular Response ◽  
Genome Wide Association Studies ◽  
Association Analyses ◽  
Genome Wide

Interferon alpha (IFNα) based therapies can induce hematologic and molecular responses in polycythemia vera (PV); however, patients do not respond equally. Germline genetic factors have previously been implicated in differential drug response. We addressed the effect of common germline polymorphisms on hematologic and molecular response (HR/MR) in PV therapy within the PROUD-PV and CONTINUATION-PV studies including 122 patients with PV receiving ropeginterferon alfa-2b. Genome-wide association studies using longitudinal data on HR and MR over 36 months follow-up did not reveal any associations at genome-wide significance. Further, we performed targeted association analyses at the interferon lambda 4 (IFNL4) locus, well known for its role in hepatitis C viral clearance and recently reported to influence HR during therapy of myeloproliferative neoplasms. While we did not observe any association of IFNL4 polymorphisms with HR in our study cohort, we demonstrated a statistically significant effect of the functionally causative IFNL4 diplotype (haplotype pair including the protein-coding variants rs368234815/rs117648444) on MR (p=3.91x10-4; OR=10.80; 95%CI:[2.39-69.97]) as reflected in differential JAK2V617F mutational burden changes according to IFNL4 diplotype status. Stratification of PV patients based on IFNL4 functionality may allow for optimizing patient management during IFNα treatment.

scholarly journals Genetic Determinants of Paget’s Disease of Bone

2021 ◽  
Author(s):  
Navnit S. Makaram ◽  
Stuart H. Ralston
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Paget’S Disease ◽  
Paget's Disease ◽  
Paget’S Disease Of Bone ◽  
Genome Wide Association Studies ◽  
Paget's Disease Of Bone ◽  
Genome Wide ◽  
Family Based

Abstract Purpose of Review To provide an overview of the role of genes and loci that predispose to Paget’s disease of bone and related disorders. Recent Findings Studies over the past ten years have seen major advances in knowledge on the role of genetic factors in Paget’s disease of bone (PDB). Genome wide association studies have identified six loci that predispose to the disease whereas family based studies have identified a further eight genes that cause PDB. This brings the total number of genes and loci implicated in PDB to fourteen. Emerging evidence has shown that a number of these genes also predispose to multisystem proteinopathy syndromes where PDB is accompanied by neurodegeneration and myopathy due to the accumulation of abnormal protein aggregates, emphasising the importance of defects in autophagy in the pathogenesis of PDB. Summary Genetic factors play a key role in the pathogenesis of PDB and the studies in this area have identified several genes previously not suspected to play a role in bone metabolism. Genetic testing coupled to targeted therapeutic intervention is being explored as a way of halting disease progression and improving outcome before irreversible skeletal damage has occurred.

scholarly journals A description of large-scale metabolomics studies: increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling

2012 ◽  
Vol 215 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Georg Homuth ◽  
Alexander Teumer ◽  
Uwe Völker ◽  
Matthias Nauck
Keyword(s):  
Blood Cells ◽  
Large Scale ◽  
Genetic Factors ◽  
Association Studies ◽  
Transcriptional Profiling ◽  
Genome Wide Association Studies ◽  
Protein Levels ◽  
Future Developments ◽  
Genome Wide ◽  
Metabolome Data

The metabolome, defined as the reflection of metabolic dynamics derived from parameters measured primarily in easily accessible body fluids such as serum, plasma, and urine, can be considered as the omics data pool that is closest to the phenotype because it integrates genetic influences as well as nongenetic factors. Metabolic traits can be related to genetic polymorphisms in genome-wide association studies, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures primarily caused by nongenetic factors. Similarly, correlation of metabolome data with transcriptional or/and proteome profiles of blood cells also produces valuable data, by revealing associations between metabolic changes and mRNA and protein levels. In the last years, the progress in correlating genetic variation and metabolome profiles was most impressive. This review will therefore try to summarize the most important of these studies and give an outlook on future developments.

Pathophysiology and genetic factors in moyamoya disease

2009 ◽  
Vol 26 (4) ◽  
pp. E4 ◽  
Author(s):  
Achal S. Achrol ◽  
Raphael Guzman ◽  
Marco Lee ◽  
Gary K. Steinberg
Keyword(s):  
Moyamoya Disease ◽  
Genetic Factors ◽  
Association Studies ◽  
Vascular Anomalies ◽  
Future Research ◽  
Incomplete Penetrance ◽  
Genome Wide Association Studies ◽  
Research Directions ◽  
Genome Wide ◽  
Future Research Directions

Moyamoya disease is an uncommon cerebrovascular condition characterized by progressive stenosis of the bilateral internal carotid arteries with compensatory formation of an abnormal network of perforating blood vessels providing collateral circulation. The etiology and pathogenesis of moyamoya disease remain unclear. Evidence from histological studies, proteomics, and endothelial progenitor cell analyses suggests new theories underlying the cause of vascular anomalies, including moyamoya disease. Familial moyamoya disease has been noted in as many as 15% of patients, indicating an autosomal dominant inheritance pattern with incomplete penetrance. Genetic analyses in familial moyamoya disease and genome-wide association studies represent promising strategies for elucidating the pathophysiology of this condition. In this review, the authors discuss recent studies that have investigated possible mechanisms underlying the etiology of moyamoya disease, including stem cell involvement and genetic factors. They also discuss future research directions that promise not only to offer new insights into the origin of moyamoya disease but to enhance our understanding of new vessel formation in the CNS as it relates to stroke, vascular anomalies, and tumor growth.

scholarly journals Bench Research Informed by GWAS Results

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3184
Author(s):  
Nikolay V. Kondratyev ◽  
Margarita V. Alfimova ◽  
Arkadiy K. Golov ◽  
Vera E. Golimbet
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Reverse Genetics ◽  
Genetic Factors ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually ‘highly polygenic’. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise ‘wet biologists’ with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

scholarly journals Identification of potential key genetic factors in the long-term success of Shigella as pathogens

2020 ◽  
Vol 2 (7A) ◽  
Author(s):  
Rebecca Bennett ◽  
Rebecca Bengtsson ◽  
Kate Baker
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Enteric Bacteria ◽  
Continuous Variable ◽  
Genome Wide Association Studies ◽  
Phenotypic Analysis ◽  
Global Management ◽  
Genome Wide ◽  
New Antibiotics

Bacterial of the genus Shigella are a major contributor to the global diarrhoea burden causing 100,000 deaths per annum globally. Further to this, increasing antibiotic resistance in Shigella and the lack of a licenced vaccine has led WHO to recognise Shigella as a priority organism for the development of new antibiotics. Understanding what drives the long-term persistence and success of this pathogen will thus aid the global management of shigellosis and may identify targets relevant to other enteric bacteria. To identify key genetic drivers of Shigella evolution over the past 100 years, we have used the historical Murray collection; comprising several hundred pre-antibiotic era (1917 – 1954) Enterobacteriaceae from diverse geographical locations. We employed genome-wide association studies to sequences from over 100 Shigella isolates from the Murray collection alongsidemore modern (i.e. 1950s – 2018) isolates to identify genetic factors (SNPs and genes) significantly associated with time as a continuous variable. GWAS hits (e.g. a putative resistance protein) then underwent variation, functional and phenotypic analysis to examine the plausibility of their role in shaping Shigella populations and as potential targets for managing this pathogen.

scholarly journals Bayesian multivariate reanalysis of large genetic studies identifies many new associations

2019 ◽  
Author(s):  
Michael C. Turchin ◽  
Matthew Stephens
Keyword(s):  
Genetic Variation ◽  
Multivariate Analyses ◽  
Association Studies ◽  
Plasma Lipid ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Traits ◽  
Association Analyses ◽  
New Associations ◽  
Genome Wide

AbstractGenome-wide association studies (GWAS) have now been conducted for hundreds of phenotypes of relevance to human health. Many such GWAS involve multiple closely-related phenotypes collected on the same samples. However, the vast majority of these GWAS have been analyzed using simple univariate analyses, which consider one phenotype at a time. This is de-spite the fact that, at least in simulation experiments, multivariate analyses have been shown to be more powerful at detecting associations. Here, we conduct multivariate association analyses on 13 different publicly-available GWAS datasets that involve multiple closely-related phenotypes. These data include large studies of anthropometric traits (GIANT), plasma lipid traits (GlobalLipids), and red blood cell traits (HaemgenRBC). Our analyses identify many new associations (433 in total across the 13 studies), many of which replicate when follow-up samples are available. Overall, our results demonstrate that multivariate analyses can help make more effective use of data from both existing and future GWAS.1Author SummaryGenome-wide association studies (GWAS) have become a common and powerful tool for identifying significant correlations between markers of genetic variation and physical traits of interest. Often these studies are conducted by comparing genetic variation against single traits one at a time (‘univariate’); however, it has previously been shown that it is possible to increase your power to detect significant associations by comparing genetic variation against multiple traits simultaneously (‘multivariate’). Despite this apparent increase in power though, researchers still rarely conduct multivariate GWAS, even when studies have multiple traits readily available. Here, we reanalyze 13 previously published GWAS using a multivariate method and find >400 additional associations. Our method makes use of univariate GWAS summary statistics and is available as a software package, thus making it accessible to other researchers interested in conducting the same analyses. We also show, using studies that have multiple releases, that our new associations have high rates of replication. Overall, we argue multivariate approaches in GWAS should no longer be overlooked and how, often, there is low-hanging fruit in the form of new associations by running these methods on data already collected.

scholarly journals A genome-wide association study on meat consumption in a Japanese population: the Japan Multi-Institutional Collaborative Cohort study

2021 ◽  
Vol 10 ◽  
Author(s):  
Yasuyuki Nakamura ◽  
Akira Narita ◽  
Yoichi Sutoh ◽  
Nahomi Imaeda ◽  
Chiho Goto ◽  
...  
Keyword(s):  
Japanese Population ◽  
Genetic Factors ◽  
Association Studies ◽  
Linear Regression Analysis ◽  
Meat Consumption ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Abstract Recent genome-wide association studies (GWAS) on the dietary habits of the Japanese population have shown that an effect rs671 allele was inversely associated with fish consumption, whereas it was directly associated with coffee consumption. Although meat is a major source of protein and fat in the diet, whether genetic factors that influence meat-eating habits in healthy populations are unknown. This study aimed to conduct a GWAS to find genetic variations that affect meat consumption in a Japanese population. We analysed GWAS data using 14 076 participants from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. We used a semi-quantitative food frequency questionnaire to estimate food intake that was validated previously. Association of the imputed variants with total meat consumption per 1000 kcal energy was performed by linear regression analysis with adjustments for age, sex, and principal component analysis components 1–10. We found that no genetic variant, including rs671, was associated with meat consumption. The previously reported single nucleotide polymorphisms that were associated with meat consumption in samples of European ancestry could not be replicated in our J-MICC data. In conclusion, significant genetic factors that affect meat consumption were not observed in a Japanese population.

ADHD genetics

2018 ◽  
Author(s):  
Kate Langley
Keyword(s):  
Genetic Factors ◽  
Rare Variants ◽  
Association Studies ◽  
Copy Number Variant ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Clinical Factors ◽  
Genome Wide ◽  
Different Types ◽  
Genetic Contributions

This chapter reviews the evidence suggesting that there is a strong genetic component to ADHD and the efforts to identify the specific genetic factors that might be involved. It discusses the different types of genetic contributions, from common to rare variants, and the evidence that these are involved in the aetiology of the disorder. An overview of the methodological strategies employed, including genome-wide association studies (GWAS), polygenic risk score, and copy number variant (CNV) analyses, is undertaken, as well as discussion of the strengths and pitfalls of such work. The contradictory findings in the field and controversies that arise as a result are also explored. Finally, this chapter considers how the heritability of ADHD and specific genetic factors involved need to be examined in the context of clinical factors such as comorbidity and how these factors affect investigations into the genetics of ADHD.

Genetic factors of polygenic urolithiasis

2020 ◽  
Vol 87 (2) ◽  
pp. 57-64
Author(s):  
Filippova Tamara Vladimirovna ◽  
Khafizov Кamil Faridovich ◽  
Rudenko Vadim Igorevich ◽  
Rapoport Leonid Mikhailovich ◽  
Tsarichenko Dmitry Georgievich ◽  
...  
Keyword(s):  
Genetic Factors ◽  
Preventive Measures ◽  
Association Studies ◽  
Case Control ◽  
International Studies ◽  
Genome Wide Association Studies ◽  
Case Control Studies ◽  
Genome Wide ◽  
Genetic Technologies ◽  
High Throughput Dna Sequencing

The article summarizes the findings of Russian and international studies of the genetic aspects of polygenic urolithiasis associated with impairment of calcium metabolism. The article analyzes the genetic risk factors of polygenic nephrolithiasis that show significant association with the disease in case-control studies and Genome-Wide Association Studies (16 genes). We described the gene functions involved in concrement formation in polygenic nephrolithiasis. The modern molecular and genetic technologies (DNA microarray, high-throughput DNA sequencing, etc.) enable identification of the genetic predisposition to a specific disease, realization of the individualized treatment of the patient, and carrying out timely preventive measures among the proband’s relatives.

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