Analysis and Application of European Genetic Substructure Using 300 K SNP Information

Tian, Chao; Plenge, Robert M.; Ransom, Michael R.; Lee, Annette; Villoslada, Pablo; Selmi, Carlo; Klareskog, Lars; Pulver, Ann E.; Qi, Lihong; Gregersen, Peter K.; Seldin, Michael F.

doi:10.1371/journal.pgen.0040004

Cited by 231 publications

(270 citation statements)

References 38 publications

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“…A recent study using PCA on GWA data in European samples 5 observed a PC that appeared to be largely because of an inversion at around location 9 Mb on chromosome 8p. This region has been identified earlier 26,27 as containing an inversion, and has LD extending over a 4 Mb region around the inversion in the samples used for this study.…”

Section: Detecting Population Differencesmentioning

confidence: 98%

Investigation of the fine structure of European populations with applications to disease association studies

Heath¹,

Gut²,

et al. 2008

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An investigation into fine-scale European population structure was carried out using high-density genetic variation on nearly 6000 individuals originating from across Europe. The individuals were collected as control samples and were genotyped with more than 300 000 SNPs in genome-wide association studies using the Illumina Infinium platform. A major East -West gradient from Russian (Moscow) samples to Spanish samples was identified as the first principal component (PC) of the genetic diversity. The second PC identified a North -South gradient from Norway and Sweden to Romania and Spain. Variation of frequencies at markers in three separate genomic regions, surrounding LCT, HLA and HERC2, were strongly associated with this gradient. The next 18 PCs also accounted for a significant proportion of genetic diversity observed in the sample. We present a method to predict the ethnic origin of samples by comparing the sample genotypes with those from a reference set of samples of known origin. These predictions can be performed using just summary information on the known samples, and individual genotype data are not required. We discuss issues raised by these data and analyses for association studies including the matching of case-only cohorts to appropriate pre-collected control samples for genome-wide association studies.

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Section: Detecting Population Differencesmentioning

confidence: 98%

Investigation of the fine structure of European populations with applications to disease association studies

Heath¹,

Gut²,

et al. 2008

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“…To discern the ancestry of Europeans or European Americans, multiple sets of AIMs have been established that allow correction for population stratification in association studies using Europeans. [5][6][7] Recently, a great number of genetic association studies on various diseases have been conducted on non-European populations.…”

Section: Introductionmentioning

confidence: 99%

A panel of ancestry informative markers to estimate and correct potential effects of population stratification in Han Chinese

Qin

Jin

et al. 2013

Eur J Hum Genet

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Population stratification acts as a confounding factor in genetic association studies and may lead to false-positive or falsenegative results. Previous studies have analyzed the genetic substructures in Han Chinese population, the largest ethnic group in the world comprising B20% of the global human population. In this study, we examined 5540 Han Chinese individuals with about 1 million single-nucleotide polymorphisms (SNPs) and screened a panel of ancestry informative markers (AIMs) to facilitate the discerning and controlling of population structure in future association studies on Han Chinese. Based on genomewide data, we first confirmed our previous observation of the north-south differentiation in Han Chinese population. Second, we developed a panel of 150 validated SNP AIMs to determine the northern or southern origin of each Han Chinese individual. We further evaluated the performance of our AIMs panel in association studies in simulation analysis. Our results showed that this AIMs panel had sufficient power to discern and control population stratification in Han Chinese, which could significantly reduce false-positive rates in both genome-wide association studies (GWAS) and candidate gene association studies (CGAS). We suggest this AIMs panel be genotyped and used to control and correct population stratification in the study design or data analysis of future association studies, especially in CGAS which is the most popular approach to validate previous reports on genetic associations of diseases in post-GWAS era.

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“…1c). However, 6 of these reside within a well-known inversion polymorphism on chromosome 8 16 . We established that all genomewide significant signals in the inversion region are attributable to the inversion, and we confirmed that the inversion is associated with neuroticism in both of our neuroticism datasets, the GPC and the UKB (Online Methods and Supplementary Note).…”

mentioning

confidence: 99%

Genetic Associations with Subjective Well-Being Also Implicate Depression and Neuroticism

Okbay

Baselmans

Neve

et al. 2015

Preprint

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We conducted genome-wide association studies of three phenotypes: subjective wellbeing (SWB; N = 298,420), depressive symptoms (DS; N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with SWB, two with DS, and eleven with neuroticism, including two inversion polymorphisms. The two DS loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (| | . ) strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association.Subjective well-being (SWB)-as measured by survey questions on life satisfaction, positive affect, or happiness-is a major topic of research within psychology, economics, and epidemiology. Twin studies have found that SWB is genetically correlated with depression (characterized by negative affect, anxiety, low energy, bodily aches and pains, pessimism, and other symptoms) and neuroticism (a personality trait characterized by easily experiencing negative emotions such as anxiety and fear) 1-3 . Depression and neuroticism have received much more attention than SWB in genetic-association studies, but the discovery of associated genetic variants with either of them has proven elusive 4,5 .In this paper, we report a series of separate and joint analyses of SWB, depressive symptoms (DS), and neuroticism. Our primary analysis is a genome-wide association study (GWAS) of SWB based on data from 59 cohorts (N = 298,420). This GWAS identifies three loci associated with SWB at genome-wide significance (p < 5×10 -8 ). We supplement this primary analysis with auxiliary GWAS meta-analyses of DS (N = 180,866) and neuroticism (N = 170,910), performed by combining publicly available summary statistics from published studies with new genome-wide analyses of additional data. In these auxiliary analyses we identify two loci associated with DS and eleven with neuroticism, including two inversion polymorphisms. In depression data from an independent sample (N = 368,890), both DS associations replicate (p = 0.004 and p = 0.015).In our two joint analyses, we exploit the high genetic correlation between SWB, DS, and neuroticism (i) to evaluate the credibility of the 16 genome-wide significant associations across the three phenotypes, and (ii) to identify novel associations (beyond those identified by the GWAS). For (i), we investigate whether our three SWB-associated SNPs "quasi-replicate" by testing them for association with DS and neuroticism. We similarly examine the quasi-replication record of the DS and neuroticism loci by testing them for association with SWB. We find that the quasi-replication record closely matches what would be expected given our statistical power if none of the genome-wide significant associations were chance findings. These results strengthen the credibility of (most of) the original associations. For (ii), we u...

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Analysis and Application of European Genetic Substructure Using 300 K SNP Information

Cited by 231 publications

References 38 publications

Investigation of the fine structure of European populations with applications to disease association studies

Investigation of the fine structure of European populations with applications to disease association studies

A panel of ancestry informative markers to estimate and correct potential effects of population stratification in Han Chinese

Genetic Associations with Subjective Well-Being Also Implicate Depression and Neuroticism

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