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1.  In search of low-frequency and rare variants affecting complex traits 
Human Molecular Genetics  2013;22(R1):R16-R21.
The allelic architecture of complex traits is likely to be underpinned by a combination of multiple common frequency and rare variants. Targeted genotyping arrays and next-generation sequencing technologies at the whole-genome sequencing (WGS) and whole-exome scales (WES) are increasingly employed to access sequence variation across the full minor allele frequency (MAF) spectrum. Different study design strategies that make use of diverse technologies, imputation and sample selection approaches are an active target of development and evaluation efforts. Initial insights into the contribution of rare variants in common diseases and medically relevant quantitative traits point to low-frequency and rare alleles acting either independently or in aggregate and in several cases alongside common variants. Studies conducted in population isolates have been successful in detecting rare variant associations with complex phenotypes. Statistical methodologies that enable the joint analysis of rare variants across regions of the genome continue to evolve with current efforts focusing on incorporating information such as functional annotation, and on the meta-analysis of these burden tests. In addition, population stratification, defining genome-wide statistical significance thresholds and the design of appropriate replication experiments constitute important considerations for the powerful analysis and interpretation of rare variant association studies. Progress in addressing these emerging challenges and the accrual of sufficiently large data sets are poised to help the field of complex trait genetics enter a promising era of discovery.
doi:10.1093/hmg/ddt376
PMCID: PMC3782074  PMID: 23922232
2.  Genome-Wide Association Study to Identify Common Variants Associated with Brachial Circumference: A Meta-Analysis of 14 Cohorts 
PLoS ONE  2012;7(3):e31369.
Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.
doi:10.1371/journal.pone.0031369
PMCID: PMC3315559  PMID: 22479309
3.  The effect of genome-wide association scan quality control on imputation outcome for common variants 
Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an input for imputing genotypes. This study aims to determine the effect of commonly applied QC steps on imputation outcomes. We performed several iterations of imputing SNPs across chromosome 22 in a dataset consisting of 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with the directly typed genotypes. In addition, we investigated the correlation between alternatively QCed data. We also applied a series of post-imputation QC steps balancing elimination of poorly imputed SNPs and information loss. We found that the difference between the unQCed data and the fully QCed data on imputation outcome was minimal. Our study shows that imputation of common variants is generally very accurate and robust to GWAS QC, which is not a major factor affecting imputation outcome. A minority of common-frequency SNPs with particular properties cannot be accurately imputed regardless of QC stringency. These findings may not generalise to the imputation of low frequency and rare variants.
doi:10.1038/ejhg.2010.242
PMCID: PMC3083623  PMID: 21267008
genome-wide association study; imputation; quality control; single nucleotide polymorphism
4.  Rare variation at the TNFAIP3 locus and susceptibility to rheumatoid arthritis 
Human Genetics  2010;128(6):627-633.
Genome-wide association studies (GWAS) conducted using commercial single nucleotide polymorphisms (SNP) arrays have proven to be a powerful tool for the detection of common disease susceptibility variants. However, their utility for the detection of lower frequency variants is yet to be practically investigated. Here we describe the application of a rare variant collapsing method to a large genome-wide SNP dataset, the Wellcome Trust Case Control Consortium rheumatoid arthritis (RA) GWAS. We partitioned the data into gene-centric bins and collapsed genotypes of low frequency variants (defined here as MAF ≤0.05) into a single count coupled with univariate analysis. We then prioritised gene regions for further investigation in an independent cohort of 3,355 cases and 2,427 controls based on rare variant signal p value and prior evidence to support involvement in RA. A total of 14,536 gene bins were investigated in the primary analysis and signals mapping to the TNFAIP3 and chr17q24 loci were selected for further investigation. We detected replicating association to low frequency variants in the TNFAIP3 gene (combined p = 6.6 × 10−6). Even though rare variants are not well-represented and can be difficult to genotype in GWAS, our study supports the application of low frequency variant collapsing methods to genome-wide SNP datasets as a means of exploiting data that are routinely ignored.
Electronic supplementary material
The online version of this article (doi:10.1007/s00439-010-0889-1) contains supplementary material, which is available to authorized users.
doi:10.1007/s00439-010-0889-1
PMCID: PMC2978888  PMID: 20852893
5.  Finding common susceptibility variants for complex disease: past, present and future 
The identification of complex disease susceptibility loci has been accelerated considerably by advances in high-throughput genotyping technologies, improved insight into correlation patterns of common variants and the availability of large-scale sample sets. Linkage scans and small-scale candidate gene studies have now given way to genome-wide association scans. In this review, we summarize insights gained from the past, highlight practical issues relating to the design and analysis of current state-of-the-art GWA studies and look into future trends in the field of human complex trait genetics.
doi:10.1093/bfgp/elp020
PMCID: PMC2758134  PMID: 19571035
association study; complex disease; single nucleotide polymorphism; genome-wide association scan; meta-analysis; sequencing
6.  No evidence of an association between mitochondrial DNA variants and osteoarthritis in 7393 cases and 5122 controls 
Annals of the Rheumatic Diseases  2012;72(1):136-139.
Objectives
Osteoarthritis (OA) has a complex aetiology with a strong genetic component. Genome-wide association studies implicate several nuclear genes in the aetiology, but a major component of the heritability has yet to be defined at the molecular level. Initial studies implicate maternally inherited variants of mitochondrial DNA (mtDNA) in subgroups of patients with OA based on gender and specific joint involvement, but these findings have not been replicated.
Methods
The authors studied 138 maternally inherited mtDNA variants genotyped in a two cohort genetic association study across a total of 7393 OA cases from the arcOGEN consortium and 5122 controls genotyped in the Wellcome Trust Case Control consortium 2 study.
Results
Following data quality control we examined 48 mtDNA variants that were common in cohort 1 and cohort 2, and found no association with OA. None of the phenotypic subgroups previously associated with mtDNA haplogroups were associated in this study.
Conclusions
We were not able to replicate previously published findings in the largest mtDNA association study to date. The evidence linking OA to mtDNA is not compelling at present.
doi:10.1136/annrheumdis-2012-201932
PMCID: PMC3551219  PMID: 22984172
Gene Polymorphism; Osteoarthritis; Pharmacogenetics
7.  Replication of Established Common Genetic Variants for Adult BMI and Childhood Obesity in Greek Adolescents: The TEENAGE Study 
Annals of Human Genetics  2013;77(3):268-274.
Multiple genetic loci have been associated with body mass index (BMI) and obesity. The aim of this study was to investigate the effects of established adult BMI and childhood obesity loci in a Greek adolescent cohort. For this purpose, 34 variants were selected for investigation in 707 (55.9% females) adolescents of Greek origin aged 13.42 ± 0.88 years. Cumulative effects of variants were assessed by calculating a genetic risk score (GRS-34) for each subject. Variants at the FTO, TMEM18, FAIM2, RBJ, ZNF608 and QPCTL loci yielded nominal evidence for association with BMI and/or overweight risk (p < 0.05). Variants at TFAP2B and NEGR1 loci showed nominal association (p < 0.05) with BMI and/or overweight risk in males and females respectively. Even though we did not detect any genome-wide significant associations, 27 out of 34 variants yielded directionally consistent effects with those reported by large-scale meta-analyses (binomial sign p = 0.0008). The GRS-34 was associated with both BMI (beta = 0.17 kg/m2/allele; p < 0.001) and overweight risk (OR = 1.09/allele; 95% CI: 1.04–1.16; p = 0.001). In conclusion, we replicate associations of established BMI and childhood obesity variants in a Greek adolescent cohort and confirm directionally consistent effects for most of them.
doi:10.1111/ahg.12012
PMCID: PMC3652032  PMID: 23347264
Obesity; BMI; common genetic variants; adolescents
8.  Evaluation of the genetic overlap between osteoarthritis with body mass index and height using genome-wide association scan data 
Annals of the Rheumatic Diseases  2012;72(6):935-941.
Objectives
Obesity as measured by body mass index (BMI) is one of the major risk factors for osteoarthritis. In addition, genetic overlap has been reported between osteoarthritis and normal adult height variation. We investigated whether this relationship is due to a shared genetic aetiology on a genome-wide scale.
Methods
We compared genetic association summary statistics (effect size, p value) for BMI and height from the GIANT consortium genome-wide association study (GWAS) with genetic association summary statistics from the arcOGEN consortium osteoarthritis GWAS. Significance was evaluated by permutation. Replication of osteoarthritis association of the highlighted signals was investigated in an independent dataset. Phenotypic information of height and BMI was accounted for in a separate analysis using osteoarthritis-free controls.
Results
We found significant overlap between osteoarthritis and height (p=3.3×10−5 for signals with p≤0.05) when the GIANT and arcOGEN GWAS were compared. For signals with p≤0.001 we found 17 shared signals between osteoarthritis and height and four between osteoarthritis and BMI. However, only one of the height or BMI signals that had shown evidence of association with osteoarthritis in the arcOGEN GWAS was also associated with osteoarthritis in the independent dataset: rs12149832, within the FTO gene (combined p=2.3×10−5). As expected, this signal was attenuated when we adjusted for BMI.
Conclusions
We found a significant excess of shared signals between both osteoarthritis and height and osteoarthritis and BMI, suggestive of a common genetic aetiology. However, only one signal showed association with osteoarthritis when followed up in a new dataset.
doi:10.1136/annrheumdis-2012-202081
PMCID: PMC3664369  PMID: 22956599
Osteoarthritis; Gene Polymorphism; Epidemiology
10.  Advances in osteoarthritis genetics 
Journal of Medical Genetics  2013;50(11):715-724.
Osteoarthritis (OA), the most common form of arthritis, is a highly debilitating disease of the joints and can lead to severe pain and disability. There is no cure for OA. Current treatments often fail to alleviate its symptoms leading to an increased demand for joint replacement surgery. Previous epidemiological and genetic research has established that OA is a multifactorial disease with both environmental and genetic components. Over the past 6 years, a candidate gene study and several genome-wide association scans (GWAS) in populations of Asian and European descent have collectively established 15 loci associated with knee or hip OA that have been replicated with genome-wide significance, shedding some light on the aetiogenesis of the disease. All OA associated variants to date are common in frequency and appear to confer moderate to small effect sizes. Some of the associated variants are found within or near genes with clear roles in OA pathogenesis, whereas others point to unsuspected, less characterised pathways. These studies have also provided further evidence in support of the existence of ethnic, sex, and joint specific effects in OA and have highlighted the importance of expanded and more homogeneous phenotype definitions in genetic studies of OA.
doi:10.1136/jmedgenet-2013-101754
PMCID: PMC3812881  PMID: 23868913
Osteoarthritis; Genetics
11.  A rare functional cardioprotective APOC3 variant has risen in frequency in distinct population isolates 
Nature Communications  2013;4:2872.
Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies, but the generalizability of such findings remains unknown. Here we genotype 1,267 individuals from a Greek population isolate on the Illumina HumanExome Beadchip, in search of functional coding variants associated with lipids traits. We find genome-wide significant evidence for association between R19X, a functional variant in APOC3, with increased high-density lipoprotein and decreased triglycerides levels. Approximately 3.8% of individuals are heterozygous for this cardioprotective variant, which was previously thought to be private to the Amish founder population. R19X is rare (<0.05% frequency) in outbred European populations. The increased frequency of R19X enables discovery of this lipid traits signal at genome-wide significance in a small sample size. This work exemplifies the value of isolated populations in successfully detecting transferable rare variant associations of high medical relevance.
Isolated populations may empower genetic association studies of complex traits. Here, the authors identify a rare cardioprotective APOC3 variant in a Greek population isolate and highlight the value of using population isolates to detect rare variants that confer disease risk.
doi:10.1038/ncomms3872
PMCID: PMC3905724  PMID: 24343240

Results 1-11 (11)