scholarly journals Genetic variants related to physical activity or sedentary behaviour: a systematic review

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Lene Aasdahl ◽  
Tom Ivar Lund Nilsen ◽  
Ingebrigt Meisingset ◽  
Anne Lovise Nordstoga ◽  
Kari Anne I. Evensen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Candidate Gene ◽  
Sedentary Behaviour ◽  
Genetic Variants ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
High Quality ◽  
Genome Wide ◽  
Candidate Gene Studies

Abstract Background Research shows that part of the variation in physical activity and sedentary behaviour may be explained by genetic factors. Identifying genetic variants associated with physical activity and sedentary behaviour can improve causal inference in physical activity research. The aim of this systematic review was to provide an updated overview of the evidence of genetic variants associated with physical activity or sedentary behaviour. Methods We performed systematic literature searches in PubMed and Embase for studies published from 1990 to April 2020 using keywords relating to “physical activity”, “exercise”, “sedentariness” and “genetics”. Physical activity phenotypes were either based on self-report (e.g., questionnaires, diaries) or objective measures (e.g., accelerometry, pedometer). We considered original studies aiming to i) identify new genetic variants associated with physical activity or sedentary behaviour (i.e., genome wide association studies [GWAS]), or ii) assess the association between known genetic variants and physical activity or sedentary behaviour (i.e., candidate gene studies). Study selection, data extraction, and critical appraisal were carried out by independent researchers, and risk of bias and methodological quality was assessed for all included studies. Results Fifty-four out of 5420 identified records met the inclusion criteria. Six of the included studies were GWAS, whereas 48 used a candidate gene approach. Only one GWAS and three candidate gene studies were considered high-quality. The six GWAS discovered up to 10 single nucleotide polymorphisms (SNPs) associated with physical activity or sedentariness that reached genome-wide significance. In total, the candidate gene studies reported 30 different genes that were associated (p < 0.05) with physical activity or sedentary behaviour. SNPs in or close to nine candidate genes were associated with physical activity or sedentary behaviour in more than one study. Conclusion GWAS have reported up to 10 loci associated with physical activity or sedentary behaviour. Candidate gene studies have pointed to some interesting genetic variants, but few have been replicated. Our review highlights the need for high-quality GWAS in large population-based samples, and with objectively assessed phenotypes, in order to establish robust genetic instruments for physical activity and sedentary behaviour. Furthermore, consistent replications in GWAS are needed to improve credibility of genetic variants. Trial registration Prospero CRD42019119456.

scholarly journals Candidate gene scan for Single Nucleotide Polymorphisms involved in the determination of normal variability in human craniofacial morphology

2016 ◽  
Author(s):  
Mark Barash ◽  
Philipp E. Bayer ◽  
Angela van Daal
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Candidate Gene ◽  
Genetic Variants ◽  
Massively Parallel Sequencing ◽  
Craniofacial Morphology ◽  
Candidate Gene Approach ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Single Nucleotide ◽  
Genome Wide

AbstractDespite intensive research on genetics of the craniofacial morphology using animal models and human craniofacial syndromes, the genetic variation that underpins normal human facial appearance is still largely elusive. Recent development of novel digital methods for capturing the complexity of craniofacial morphology in conjunction with high-throughput genotyping methods, show great promise for unravelling the genetic basis of such a complex trait.As a part of our efforts on detecting genomic variants affecting normal craniofacial appearance, we have implemented a candidate gene approach by selecting 1,201 single nucleotide polymorphisms (SNPs) and 4,732 tag SNPs in over 170 candidate genes and intergenic regions. We used 3-dimentional (3D) facial scans and direct cranial measurements of 587 volunteers to calculate 104 craniofacial phenotypes. Following genotyping by massively parallel sequencing, genetic associations between 2,332 genetic markers and 104 craniofacial phenotypes were tested.An application of a Bonferroni–corrected genome–wide significance threshold produced significant associations between five craniofacial traits and six SNPs. Specifically, associations of nasal width with rs8035124 (15q26.1), cephalic index with rs16830498 (2q23.3), nasal index with rs37369 (5q13.2), transverse nasal prominence angle with rs59037879 (10p11.23) and rs10512572 (17q24.3), and principal component explaining 73.3% of all the craniofacial phenotypes, with rs37369 (5p13.2) and rs390345 (14q31.3) were observed.Due to over-conservative nature of the Bonferroni correction, we also report all the associations that reached the traditional genome-wide p-value threshold (<5.00E-08) as suggestive. Based on the genome-wide threshold, 8 craniofacial phenotypes demonstrated significant associations with 34 intergenic and extragenic SNPs. The majority of associations are novel, except PAX3 and COL11A1 genes, which were previously reported to affect normal craniofacial variation.This study identified the largest number of genetic variants associated with normal variation of craniofacial morphology to date by using a candidate gene approach, including confirmation of the two previously reported genes. These results enhance our understanding of the genetics that determines normal variation in craniofacial morphology and will be of particular value in medical and forensic fields.Author SummaryThere is a remarkable variety of human facial appearances, almost exclusively the result of genetic differences, as exemplified by the striking resemblance of identical twins. However, the genes and specific genetic variants that affect the size and shape of the cranium and the soft facial tissue features are largely unknown. Numerous studies on animal models and human craniofacial disorders have identified a large number of genes, which may regulate normal craniofacial embryonic development.In this study we implemented a targeted candidate gene approach to select more than 1,200 polymorphisms in over 170 genes that are likely to be involved in craniofacial development and morphology. These markers were genotyped in 587 DNA samples using massively parallel sequencing and analysed for association with 104 traits generated from 3-dimensional facial images and direct craniofacial measurements. Genetic associations (p-values<5.00E-08) were observed between 8 craniofacial traits and 34 single nucleotide polymorphisms (SNPs), including two previously described genes and 26 novel candidate genes and intergenic regions. This comprehensive candidate gene study has uncovered the largest number of novel genetic variants affecting normal facial appearance to date. These results will appreciably extend our understanding of the normal and abnormal embryonic development and impact our ability to predict the appearance of an individual from a DNA sample in forensic criminal investigations and missing person cases.

scholarly journals The genetic overlap between mood disorders and cardio-metabolic diseases: A systematic review of genome wide and candidate gene studies

2017 ◽  
Author(s):  
Azmeraw T. Amare ◽  
Klaus Oliver Schubert ◽  
Sarah Cohen-Woods ◽  
Bernhard T. Baune
Keyword(s):  
Candidate Gene ◽  
Mood Disorders ◽  
Metabolic Diseases ◽  
Association Studies ◽  
Lithium Treatment ◽  
Axonal Guidance ◽  
Genome Wide Association Studies ◽  
R Genes ◽  
Genome Wide ◽  
Candidate Gene Studies

ABSTRACTMeta-analyses of genome-wide association studies (meta-GWAS) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases, and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardio-metabolic diseases risk (CMD-R) genes that are also associated with mood disorders. Firstly, we reviewed meta-GWA studies published until January 2016, for the diseases “type 2 diabetes, coronary artery disease, hypertension” and/or for the risk factors “blood pressure, obesity, plasma lipid levels, insulin and glucose related traits”. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and “depressive disorder” OR “depressive symptoms” OR “bipolar disorder” OR “lithium treatment”, OR “serotonin reuptake inhibitors treatment”. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B, and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin and dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our findings provide insights in to the shared biological mechanisms of mood disorders and cardio-metabolic diseases.

Genetics of osteoarthritis

2013 ◽  
pp. 331-335
Author(s):  
Alex MacGregor ◽  
Ana Valdes ◽  
Frances M. K. Williams
Keyword(s):  
Genetic Variants ◽  
Joint Pain ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Pain Processing ◽  
Main Symptom ◽  
Asian Populations ◽  
Genome Wide ◽  
Candidate Gene Studies ◽  
Related Individuals

In this chapter we outline the approaches which have been adopted to identify genetic variants predisposing to osteoarthritis (OA), a condition long recognized as having a heritable component. Such routes to their identification include examining mendelian traits in which OA is a feature, candidate gene studies based on knowledge of OA pathobiology, linkage analysis in related individuals, and, more recently, genome-wide association studies in large samples of unrelated individuals. It is increasingly evident that the main symptom deriving from OA—notably joint pain—also has a genetic basis but this is differs from that underlying OA. Variants convincingly shown to predispose to OA lie in the GDF5 and MCF2L genes and in the chr7 cluster mapping to the COG5 gene, in addition to the ASPN gene in Asian populations. Those associated with pain in OA include TRPV1 and PACE4. Epigenetic influences are also being explored in both the pathogenesis of OA and the variation of pain processing.

scholarly journals Modifiable lifestyle factors and severe COVID-19 risk: a Mendelian randomisation study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Shuai Li ◽  
Xinyang Hua
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Association Studies ◽  
Lifestyle Factors ◽  
Mendelian Randomisation ◽  
Severe Illness ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk

Abstract Background Lifestyle factors including obesity and smoking are suggested to be correlated with increased risk of COVID-19 severe illness or related death. However, whether these relationships are causal is not well known; neither for the relationships between COVID-19 severe illness and other common lifestyle factors, such as physical activity and alcohol consumption. Methods Genome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, physical activity and alcohol consumption identified by large-scale genome-wide association studies (GWAS) of up to 941,280 individuals were selected as instrumental variables. Summary statistics of the genetic variants on severe illness of COVID-19 were obtained from GWAS analyses of up to 6492 cases and 1,012,809 controls. Two-sample Mendelian randomisation analyses were conducted. Results Both per-standard deviation (SD) increase in genetically predicted BMI and lifetime smoking were associated with about two-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P < 0.05). Per-SD increase in genetically predicted physical activity was associated with decreased risks of severe respiratory COVID-19 (odds ratio [OR] = 0.19; 95% confidence interval [CI], 0.05, 0.74; P = 0.02), but not with COVID-19 hospitalization (OR = 0.44; 95% CI 0.18, 1.07; P = 0.07). No evidence of association was found for genetically predicted alcohol consumption. Similar results were found across robust Mendelian randomisation methods. Conclusions Evidence is found that BMI and smoking causally increase and physical activity might causally decrease the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

scholarly journals Modifiable lifestyle factors and severe COVID-19 risk: Evidence from Mendelian randomization analysis

2020 ◽  
Author(s):  
Shuai Li
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Lifestyle Factors ◽  
Severe Illness ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk

AbstractBackgroundLifestyle factors including obesity and smoking are suggested to be related to increased risk of COVID-19 severe illness or related death. However, little is known about whether these relationships are causal, or the relationships between COVID-19 severe illness and other lifestyle factors, such as alcohol consumption and physical activity.MethodsGenome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, alcohol consumption and physical activity identified by large-scale genome-wide association studies (GWAS) were selected as instrumental variables. GWAS summary statistics of these genetic variants for relevant lifestyle factors and severe illness of COVID-19 were obtained. Two-sample Mendelian randomization (MR) analyses were conducted.ResultsBoth genetically predicted BMI and lifetime smoking were associated with about 2-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P<0.05). Genetically predicted physical activity was associated with about 5-fold (95% confidence interval [CI], 1.4, 20.3; P=0.02) decreased risk of severe respiratory COVID-19, but not with COVID-19 hospitalization, though the majority of the 95% CI did not include one. No evidence of association was found for genetically predicted alcohol consumption, but associations were found when using pleiotropy robust methods.ConclusionEvidence is found that BMI and smoking causally increase and physical activity causally decreases the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

scholarly journals Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results

2011 ◽  
Vol 42 (3) ◽  
pp. 607-616 ◽  
Author(s):  
A. L. Collins ◽  
Y. Kim ◽  
P. Sklar ◽  
M. C. O'Donovan ◽  
P. F. Sullivan ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Association Studies ◽  
Human Diseases ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Common Genetic Variation ◽  
Genome Wide ◽  
Candidate Gene Studies

BackgroundCandidate gene studies have been a key approach to the genetics of schizophrenia (SCZ). However, the results of these studies are confusing and no genes have been unequivocally implicated. The hypothesis-driven candidate gene literature can be appraised by comparison with the results of genome-wide association studies (GWAS).MethodWe describe the characteristics of hypothesis-driven candidate gene studies from the SZGene database, and use pathway analysis to compare hypothesis-driven candidate genes with GWAS results from the International Schizophrenia Consortium (ISC).ResultsSZGene contained 732 autosomal genes evaluated in 1374 studies. These genes had poor statistical power to detect genetic effects typical for human diseases, assessed only 3.7% of genes in the genome, and had low marker densities per gene. Most genes were assessed once or twice (76.9%), providing minimal ability to evaluate consensus across studies. The ISC studies had 89% power to detect a genetic effect typical for common human diseases and assessed 79% of known autosomal common genetic variation. Pathway analyses did not reveal enrichment of smaller ISCpvalues in hypothesis-driven candidate genes, nor did a comprehensive evaluation of meta-hypotheses driving candidate gene selection (SCZ as a disease of the synapse or neurodevelopment). The most studied hypothesis-driven candidate genes (COMT,DRD3,DRD2,HTR2A,NRG1,BDNF,DTNBP1andSLC6A4) had no notable ISC results.ConclusionsWe did not find support for the idea that the hypothesis-driven candidate genes studied in the literature are enriched for the common genetic variation involved in the etiology of SCZ. Larger samples are required to evaluate this conclusion definitively.

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