scholarly journals Genetics and genomics of human ageing

2011 ◽  
Vol 366 (1561) ◽  
pp. 43-50 ◽  
Author(s):  
Heather E. Wheeler ◽  
Stuart K. Kim
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Transcriptional Profiling ◽  
Genetic Association Studies ◽  
Human Kidney ◽  
Age Related ◽  
Quantitative Trait Mapping ◽  
Human Ageing ◽  
Probability Of Death ◽  
Genomic Convergence

Ageing in humans is typified by the decline of physiological functions in various organs and tissues leading to an increased probability of death. Some individuals delay, escape or survive much of this age-related decline and live past age 100. Studies comparing centenarians to average-aged individuals have found polymorphisms in genes that are associated with long life, including APOE and FOXOA3 , which have been replicated many times. However, the associations found in humans account for small percentages of the variance in lifespan and many other gene associations have not been replicated in additional populations. Therefore, ageing is probably a highly polygenic trait. In humans, it is important to also consider differences in age-related decline that occur within and among tissues. Longitudinal data of age-related traits can be used in association studies to test for polymorphisms that predict how an individual will change over time. Transcriptional and genetic association studies of different tissues have revealed common and unique pathways involved in human ageing. Genomic convergence is a method that combines multiple types of functional genomic information such as transcriptional profiling, expression quantitative trait mapping and gene association. The genomic convergence approach has been used to implicate the gene MMP20 in human kidney ageing. New human genetics technologies are continually in development and may lead to additional breakthroughs in human ageing in the near future.

scholarly journals A Validated Phenotyping Algorithm for Genetic Association Studies in Age-related Macular Degeneration

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Joseph M. Simonett ◽  
Mahsa A. Sohrab ◽  
Jennifer Pacheco ◽  
Loren L. Armstrong ◽  
Margarita Rzhetskaya ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Age Related Macular Degeneration ◽  
Age Related

scholarly journals Human Ageing Genomic Resources: 2018 Update

2017 ◽  
Author(s):  
Robi Tacutu ◽  
Daniel Thornton ◽  
Emily Johnson ◽  
Arie Budovsky ◽  
Diogo Barardo ◽  
...  
Keyword(s):  
Association Studies ◽  
Genetic Association Studies ◽  
Quality Data ◽  
Model Organisms ◽  
High Quality Data ◽  
External Resources ◽  
Genomic Resources ◽  
Online Resource ◽  
Human Ageing ◽  
Cross Links

AbstractIn spite of a growing body of research and data, human ageing remains a poorly understood process. To facilitate studies of ageing, over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), which are now the leading online resource for biogerontologists. In this update, we present HAGR’s main functionalities, including new additions and improvements to HAGR. HAGR consists of five databases: 1) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; 2) the AnAge database of animal ageing and longevity, featuring >4000 species; 3) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; 4) the LongevityMap database of human genetic association studies of longevity with >500 entries; 5) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; 6) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts to ensure a high quality data and presented in an intuitive and clear interface that includes cross-links across our databases and to external resources. HAGR is freely available online (http://genomics.senescence.info/).

scholarly journals Big DNA as a tool to dissect an age-related macular degeneration-associated haplotype

2018 ◽  
Author(s):  
Jon M Laurent ◽  
Xin Fu ◽  
Sergei German ◽  
Matthew T Maurano ◽  
Kang Zhang ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Cell Types ◽  
Difficult Problem ◽  
Age Related Macular Degeneration ◽  
Functional Sites ◽  
Functional Variants ◽  
Age Related ◽  
Aging Populations

AbstractAge-related Macular Degeneration (AMD) is a leading cause of blindness in the developed world, especially in aging populations, and is therefore an important target for new therapeutic development. Recently, there have been several studies demonstrating strong associations between AMD and sites of heritable genetic variation at multiple loci, including a highly significant association at 10q26. The 10q26 risk region contains two genes, HTRA1 and ARMS2, both of which have been separately implicated as causative for the disease, as well as dozens of sites of non-coding variation. To date, no studies have successfully pinpointed which of these variant sites are functional in AMD, nor definitively identified which genes in the region are targets of such regulatory variation. In order to efficiently decipher which sites are functional in AMD phenotypes, we describe a general framework for combinatorial assembly of large ‘synthetic haplotypes’ along with delivery to relevant disease cell types for downstream functional analysis. We demonstrate the successful and highly efficient assembly of a first-draft 119kb wild-type ‘assemblon’ covering the HTRA1/ARMS2 risk region. We further propose the parallelized assembly of a library of combinatorial variant synthetic haplotypes covering the region, delivery and analysis of which will identify functional sites and their effects, leading to an improved understanding of AMD development. We anticipate that the methodology proposed here is highly generalizable towards the difficult problem of identifying truly functional variants from those discovered via GWAS or other genetic association studies.

scholarly journals A Compendium of Age-Related PheWAS and GWAS Traits for Human Genetic Association Studies, Their Networks and Genetic Correlations

2021 ◽  
Vol 12 ◽  
Author(s):  
Seung-Soo Kim ◽  
Adam D. Hudgins ◽  
Brenda Gonzalez ◽  
Sofiya Milman ◽  
Nir Barzilai ◽  
...  
Keyword(s):  
Genetic Association ◽  
Heart Diseases ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genetic Association Studies ◽  
Brain Diseases ◽  
Genome Wide Association Studies ◽  
Medical Subject Headings ◽  
Age Related ◽  
Rich Data

The rich data from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) offer an unprecedented opportunity to identify the biological underpinnings of age-related disease (ARD) risk and multimorbidity. Surprisingly, however, a comprehensive list of ARDs remains unavailable due to the lack of a clear definition and selection criteria. We developed a method to identify ARDs and to provide a compendium of ARDs for genetic association studies. Querying 1,358 electronic medical record-derived traits, we first defined ARDs and age-related traits (ARTs) based on their prevalence profiles, requiring a unimodal distribution that shows an increasing prevalence after the age of 40 years, and which reaches a maximum peak at 60 years of age or later. As a result, we identified a list of 463 ARDs and ARTs in the GWAS and PheWAS catalogs. We next translated the ARDs and ARTs to their respective 276 Medical Subject Headings diseases and 45 anatomy terms. The most abundant disease categories are neoplasms (48 terms), cardiovascular diseases (44 terms), and nervous system diseases (27 terms). Employing data from a human symptoms-disease network, we found 6 symptom-shared disease groups, representing cancers, heart diseases, brain diseases, joint diseases, eye diseases, and mixed diseases. Lastly, by overlaying our ARD and ART list with genetic correlation data from the UK Biobank, we found 54 phenotypes in 2 clusters with high genetic correlations. Our compendium of ARD and ART is a highly useful resource, with broad applicability for studies of the genetics of aging, ARD, and multimorbidity.

scholarly journals Sequential Use of Transcriptional Profiling, Expression Quantitative Trait Mapping, and Gene Association Implicates MMP20 in Human Kidney Aging

PLoS Genetics ◽  
2009 ◽  
Vol 5 (10) ◽  
pp. e1000685 ◽  
Author(s):  
Heather E. Wheeler ◽  
E. Jeffrey Metter ◽  
Toshiko Tanaka ◽  
Devin Absher ◽  
John Higgins ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Transcriptional Profiling ◽  
Human Kidney ◽  
Gene Association ◽  
Trait Mapping ◽  
Quantitative Trait Mapping

scholarly journals Human genetics of tuberculosis: a long and winding road

2014 ◽  
Vol 369 (1645) ◽  
pp. 20130428 ◽  
Author(s):  
Laurent Abel ◽  
Jamila El-Baghdadi ◽  
Ahmed Aziz Bousfiha ◽  
Jean-Laurent Casanova ◽  
Erwin Schurr
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Single Gene ◽  
Genetic Association Studies ◽  
Epidemiological Studies ◽  
Interferon Γ ◽  
Past Century ◽  
Inborn Errors ◽  
Novel Treatments ◽  
The Past

Only a small fraction of individuals exposed to Mycobacterium tuberculosis develop clinical tuberculosis (TB). Over the past century, epidemiological studies have shown that human genetic factors contribute significantly to this interindividual variability, and molecular progress has been made over the past decade for at least two of the three key TB-related phenotypes: (i) a major locus controlling resistance to infection with M. tuberculosis has been identified, and (ii) proof of principle that severe TB of childhood can result from single-gene inborn errors of interferon-γ immunity has been provided; genetic association studies with pulmonary TB in adulthood have met with more limited success. Future genetic studies of these three phenotypes could consider subgroups of subjects defined on the basis of individual (e.g. age at TB onset) or environmental (e.g. pathogen strain) factors. Progress may also be facilitated by further methodological advances in human genetics. Identification of the human genetic variants controlling the various stages and forms of TB is critical for understanding TB pathogenesis. These findings should have major implications for TB control, in the definition of improved prevention strategies, the optimization of vaccines and clinical trials and the development of novel treatments aiming to restore deficient immune responses.

scholarly journals Improved Score Statistics for Meta-analysis in Single-variant and Gene-level Association Studies

2017 ◽  
Author(s):  
Jingjing Yang ◽  
Sai Chen ◽  
Gonçalo Abecasis ◽  
Keyword(s):  
Power Loss ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Association Studies ◽  
Age Related Macular Degeneration ◽  
Joint Analysis ◽  
Analysis Methods ◽  
Age Related ◽  
Score Statistics ◽  
Gene Level

AbstractMeta-analysis is now an essential tool for genetic association studies, allowing these to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate why the standard meta-analysis methods lose power under unbalanced settings, and further propose a novel meta-analysis method that performs as efficiently as joint analysis under general settings. Our proposed method can accurately approximate the score statistics obtainable by joint analysis, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies (MAFs). In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard method. We further showed the power gain of our method in gene-level association studies with 26 unbalanced real studies of Age-related Macular Degeneration (AMD). In addition, we took the meta-analysis of three studies of type 2 diabetes (T2D) as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, we propose improved single-variant score statistics in meta-analysis, requiring “accurate” population-specific MAFs for multi-ethnic studies. These improved score statistics can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses.

scholarly journals dbGSRV: a manually curated database of genetic susceptibility to respiratory virus

2021 ◽  
Author(s):  
Ping Li ◽  
Yan Zhang ◽  
Wenlong Shen ◽  
Shu Shi ◽  
Zhihu Zhao
Keyword(s):  
Virus Infection ◽  
Genetic Susceptibility ◽  
Drug Targets ◽  
Respiratory Virus ◽  
Human Genetics ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Respiratory Viruses ◽  
Reference Information ◽  
Respiratory Virus Infection

Human genetics has been proposed to play an essential role in inter-individual differences in respiratory virus infection occurrence and outcomes. To systematically understand human genetic contributions to respiratory virus infection, we developed the database dbGSRV, a manually curated database that integrated the host genetic susceptibility and severity studies of respiratory viruses scattered over literatures in PubMed. At present, dbGSRV contains 1932 records of genetic association studies relating 1010 unique variants and seven respiratory viruses, manually curated from 168 published articles. Users can access the records by quick searching, batch searching, advanced searching and browsing. Reference information, infection status, population information, mutation information and disease relationship are provided for each record, as well as hyper links to public databases in convenient of users accessing more information. In addition, a visual overview of the topological network relationship between respiratory viruses and associated genes is provided. Therefore, dbGSRV offers a promising avenue to facilitate researchers to dissect human factors in respiratory virus infection, define novel drug targets, conduct risk stratification of population and develop personalized medicine approaches. Database URL: http://www.ehbio.com/dbGSRV/front/

scholarly journals Human Genetics to Identify Therapeutic Targets for NAFLD: Challenges and Opportunities

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaomi Du ◽  
Natalie DeForest ◽  
Amit R. Majithia
Keyword(s):  
Human Genetics ◽  
Target Identification ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Diagnostic Methods ◽  
Genetic Associations ◽  
Alcoholic Fatty Liver ◽  
Diagnostic Measures ◽  
Challenges And Opportunities ◽  
Continuous Progression

Non-alcoholic fatty liver disease (NAFLD) is a continuous progression of pathophysiologic stages that is challenging to diagnose due to its inherent heterogeneity and poor standardization across a wide variety of diagnostic measures. NAFLD is heritable, and several loci have been robustly associated with various stages of disease. In the past few years, larger genetic association studies using new methodology have identified novel genes associated with NAFLD, some of which have shown therapeutic promise. This mini-review provides an overview of the heterogeneity in NAFLD phenotypes and diagnostic methods, discusses genetic associations in relation to the specific stages for which they were identified, and offers a perspective on the design of future genetic mapping studies to accelerate therapeutic target identification.

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