Burden of Common Complex Disease Variants in the Exomes of Two Healthy Centenarian Brothers

Gerontology ◽  
2015 ◽  
Vol 62 (1) ◽  
pp. 58-62 ◽  
Author(s):  
Lauren C. Tindale ◽  
Andy Zeng ◽  
Karla L. Bretherick ◽  
Stephen Leach ◽  
Nina Thiessen ◽  
...  
Keyword(s):  
Complex Disease ◽  
Common Complex Disease ◽  
Healthy Centenarian

scholarly journals Genetic Vectors as a Tool in Association Studies: Definitions and Application for Study of Rheumatoid Arthritis

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Igor Sandalov ◽  
Leonid Padyukov
Keyword(s):  
Rheumatoid Arthritis ◽  
Complex Disease ◽  
Association Studies ◽  
Healthy Population ◽  
Common Complex Disease ◽  
New Approach ◽  
Functional Studies ◽  
Biological Interpretation ◽  
Genetic Vectors ◽  
Efficient Selection

To identify putative relations between different genetic factors in the human genome in the development of common complex disease, we mapped the genetic data to an ensemble of spin chains and analysed the data as a quantum system. Each SNP is considered as a spin with three states corresponding to possible genotypes. The combined genotype represents a multispin state, described by the product of individual-spin states. Each person is characterized by a single genetic vector (GV) and individuals with identical GVs comprise the GV group. This consolidation of genotypes into GVs provides integration of multiple genetic variants for a single statistical test and excludes ambiguity of biological interpretation known for allele and haplotype associations. We analyzed two independent cohorts, with 2633 rheumatoid arthritis cases and 2108 healthy controls, and data for 6 SNPs from the HTR2A locus plus shared epitope allele. We found that GVs based on selected markers are highly informative and overlap for 98.3% of the healthy population between two cohorts. Interestingly, some of the GV groups contain either only controls or only cases, thus demonstrating extreme susceptibility or protection features. By using this new approach we confirmed previously detected univariate associations and demonstrated the most efficient selection of SNPs for combined analyses for functional studies.

scholarly journals OsteoporosAtlas: a human osteoporosis-related gene database

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6778 ◽  
Author(s):  
Xun Wang ◽  
Lihong Diao ◽  
Dezhi Sun ◽  
Dan Wang ◽  
Jiarun Zhu ◽  
...  
Keyword(s):  
Complex Disease ◽  
Treatment Strategies ◽  
Osteoporotic Fractures ◽  
Relevant Information ◽  
Extensive Literature ◽  
Mineral Density ◽  
Common Complex Disease ◽  
Increased Risk ◽  
Prevention And Treatment ◽  
Pathway Analyses

Background Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs. Methods We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server. Results OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies.

scholarly journals Multi-locus interactions predict risk for post-PTCA restenosis: an approach to the genetic analysis of common complex disease

2002 ◽  
Vol 2 (3) ◽  
pp. 197-201 ◽  
Author(s):  
R Y L Zee ◽  
J Hoh ◽  
S Cheng ◽  
R Reynolds ◽  
M A Grow ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Complex Disease ◽  
Common Complex Disease

scholarly journals Construction of gene clusters resembling genetic causal mechanisms for common complex disease with an application to young-onset hypertension

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 497 ◽  
Author(s):  
Ke-Shiuan Lynn ◽  
Chen-Hua Lu ◽  
Han-Ying Yang ◽  
Wen-Lian Hsu ◽  
Wen-Harn Pan
Keyword(s):  
Complex Disease ◽  
Gene Clusters ◽  
Common Complex Disease ◽  
Young Onset ◽  
Causal Mechanisms

scholarly journals Risk Factors for Coronary Artery Diseases: A Study Among Patients With Ischemic Heart Disease in India (Kerala)

2013 ◽  
Vol 6 (2) ◽  
pp. 118-124
Author(s):  
Cyril James ◽  
Thankachan V. Attacheril ◽  
N. Balakrishnan ◽  
Diana K. Gaydarova ◽  
Nadya Y. Stancheva ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Indian Population ◽  
Complex Disease ◽  
Stress Test ◽  
Common Complex Disease ◽  
Coronary Syndrome ◽  
Artery Disease

Summary Coronary artery disease (CAD) is a condition that develops due to accumulation of atherosclerotic plaque in the epicardial coronary arteries, leading to myocardial ischemia. It is the leading cause of death worldwide and is a common complex disease. A study was carried out in a group of 496 patients with acute coronary syndrome or with angiographic or stress test evidence for coronary artery disease, admitted to the Department of Cardiology at Lourdes Heart Institute and Neuro Centre during the period June-August 2012. The risk factors studied were hypertension, diabetes mellitus, dyslipidemia, body mass index, smoking and family history of CAD. The results demonstrated that in both males and females of the Indian population studies, diabetes and dyslipidemia were major risk factors for CAD, while hypertension was not a major risk factor. Therefore, early detection and treatment of diabetes mellitus and dyslipidemia play a vital role in prevention of CAD in Indian population.

scholarly journals Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins

2021 ◽  
Author(s):  
Jenny C. Censin ◽  
Jonas Bovijn ◽  
Michael V. Holmes ◽  
Cecilia M. Lindgren
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Psychological Health ◽  
Complex Disease ◽  
Genome Wide Association Study ◽  
Disease Risk ◽  
Polycystic Ovary ◽  
European Ancestry ◽  
Common Complex Disease ◽  
Ovary Syndrome ◽  
A Genome

AbstractPolycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology.

scholarly journals Allele-specific transcript abundance: A pilot study in healthy centenarians

2019 ◽  
Author(s):  
Lauren C. Tindale ◽  
Nina Thiessen ◽  
Stephen Leach ◽  
Angela R. Brooks-Wilson
Keyword(s):  
Pilot Study ◽  
Healthy Aging ◽  
Complex Disease ◽  
Transcript Abundance ◽  
Common Complex Disease ◽  
Small Pilot Study ◽  
Risk Variants ◽  
Allele Specific ◽  
Disease Associated Genes ◽  
Cell Fractions

AbstractThe genetic basis of healthy aging and longevity remains largely unexplained. One hypothesis as to why long-lived individuals do not appear to have a lower number of common-complex disease variants, is that despite carrying risk variants, they express disease-linked alleles at a lower level than the wild-type alleles. Allele-specific abundance (ASA) is the different transcript abundance of the two haplotypes of a diploid individual. We sequenced the transcriptomes of four healthy centenarians and four mid-life controls. CIBERSORT was used to estimate blood cell fractions: neutrophils were the most abundant source of RNA, followed by CD8+ T cells, resting NK cells, and monocytes. ASA variants were more common in non-coding than coding regions. Centenarians and controls had a comparable distribution of ASA variants by predicted effect, and we did not observe an overall bias in expression towards major or minor alleles. Immune pathways were most highly represented among the gene set that showed ASA. Although we found evidence of ASA in disease-associated genes and transcription factors, we did not observe any differences in the pattern of expression between centenarians and controls in this small pilot study.

Familial combined hyperlipidaemia: how can genetic disorders be common, complex and comprehensible?

2007 ◽  
Vol 113 (9) ◽  
pp. 365-367 ◽  
Author(s):  
Allan Sniderman ◽  
Swneke D. Bailey ◽  
C. Jamie Engert
Keyword(s):  
Metabolic Pathways ◽  
Complex Disease ◽  
Genetic Disorders ◽  
Common Complex Disease ◽  
Multiple Gene ◽  
Multiple Phenotypes ◽  
Multiple Phenotype ◽  
Multiple Pathway ◽  
Energy Excess

FCHL (familial combined hyperlipidaemia) is characterized by multiple phenotypes that are shaped by genes, the environment and time. A longitudinal study by Brouwers and co-workers, which appears in this issue of Clinical Science, points to the central role of the liver in defining the FCHL phenotypes and demonstrates how they vary over time in relation to energy excess. On the basis of their work and that of others, we propose that FCHL is a multiple gene/multiple pathway/multiple phenotype disease. The key feature of this model of common complex disease is that it posits testable faults in definable metabolic pathways, which supply the genetic underpinning of the disorder.

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