Set Of Ancestry Informative Markers Research Articles

Global and local ancestry estimation in a captive baboon colony.

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

Abstract 766: Genomic and transcriptomic comparison between breast cancers from patients of African and European genetically determined ancestries demonstrates potential for ancestry specific biomarker-informed therapies

Abstract Background: Therapeutic approaches for breast cancer (BC) are informed by tumor subtypes and molecular heterogeneity, both of which may be associated with particular patient ancestries. While patients of African ancestry (AA) exhibit a relatively high mortality rate compared with patients of European ancestry (EA), the biological underpinnings of this disparity are not entirely understood. Here, we present a genomic and transcriptomic comparison between BC tumors from AA and EA patients stratified by clinical features in a real-world cohort. Methods: De-identified records from AA (n=629) and EA (n=2832) patients with BC were selected from the Tempus Oncology Database. All tumors underwent sequencing with the Tempus|xT assay, including targeted-panel DNA and full-transcriptome RNA-seq. Race metadata was obtained from abstracted records. Genetic ancestry was estimated using a set of ancestry-informative markers and a supervised version of the ADMIXTURE algorithm. Mutational prevalence, gene expression, and transcriptional signatures were compared between EA and AA groups, and stratified by stage and subtype. Statistical significance was assessed with Bonferroni correction applied to adjust for multiple testing. Results: Genetic ancestry estimates and race metadata had strong concordance, with 97% and 91% of race data matching genetic ancestry categories in AA and EA, respectively. Compared to EA patients, AA patients were slightly younger (median age 53.8 years vs. 56.1 years) and more likely to have stage IV disease (59.0% vs. 56.5%). The percentage of triple-negative BC (TNBC) patients was much higher among AA (23.5%) compared to EA (14.3%), while the proportion of HR+/HER2− patients was higher in EA (46.4%) compared to AA (36.5%). In HR+/HER2- patients, AA patients had a higher prevalence of KMT2C (24% vs. 14%), GATA3 (21% vs. 14%), and FGFR1 (18% vs. 12%) mutations, and a lower prevalence of PIK3CA (33% vs. 42%) and PTEN (6% vs. 13%) mutations. PRSS23 expression and estrogen response late signaling were significantly downregulated in late-stage HR+/HER2- AA patients, while PTEN signaling was downregulated in stages I-III. Among TNBC, AA patients had a higher prevalence of KMT2C (23% vs. 12%) mutations. LILRA6 and PTEN were significantly downregulated in early-stage TNBC patients of AA. Conclusions: After controlling for stage at diagnosis and subtype, we observed significant differences in BC mutational spectrums, gene expression, and relevant pathway activities between patients with genetically determined AA and EA, particularly within the TNBC and HR+/HER2- subtypes. These findings may guide future development of treatment strategies by providing data for biomarker-informed research and precision cancer care. Citation Format: Minoru Miyashita, Joshua S. Bell, Ezgi Karaesmen, Brooke Rhead, Stephane Wenric, Kristiyana Kaneva, Francisco M. De La Vega, Yonglan Zheng, Toshio Yoshimatsu, Galina Khramtsova, Elisabeth Sveen, Fang Liu, Fangyuan Zhao, Frederick Howard, Nora T. Jaskowiak, Rita Nanda, Dezheng Huo, Olufunmilayo I. Olopade. Genomic and transcriptomic comparison between breast cancers from patients of African and European genetically determined ancestries demonstrates potential for ancestry specific biomarker-informed therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 766.

Identification of Wolf-Dog Hybrids in Europe – An Overview of Genetic Studies

Significant development of genetic tools during the last decades provided opportunities for more detailed analyses and deeper understanding of species hybridization. New genetic markers allowed for reliable identification of admixed individuals deriving from recent hybridization events (a few generations) and those originating from crossings up to 19 generations back. Implementation of microsatellites (STRs) together with Bayesian clustering provided abundant knowledge regarding presence of admixed individuals in numerous populations and helped understand the problematic nature of studying hybridization (i.a., defining a reliable thresholds for recognizing individuals as admixed or obtaining well-grounded results representing actual proportion of hybrids in a population). Nevertheless, their utilization is limited to recent crossbreeding events. Single Nucleotide Polymorphisms (SNPs) proved to be more sensible tools for admixture analyses furnishing more reliable knowledge, especially for older generation backcrosses. Small sets of Ancestry Informative Markers (AIMs) of both types of markers were effective enough to implement in monitoring programs, however, SNPs seem to be more appropriate because of their ability to identify admixed individuals up to 3rd generations. The main aim of this review is to summarize abundant knowledge regarding identification of wolf-dog hybrids in Europe and discuss the most relevant problems relating to the issue, together with advantages and disadvantages of implemented markers and approaches.

Genetic Consequences of the Transatlantic Slave Trade in the Americas

According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery’s abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which—combined with historical shipping documents—illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.

How to choose sets of ancestry informative markers: A supervised feature selection approach

Inference of the Biogeographical Ancestry (BGA) of a person or trace relies on three ingredients: (1) a reference database of DNA samples including BGA information; (2) a statistical clustering method; (3) a set of loci which segregate dependent on geographical location, i.e. a set of so-called Ancestry Informative Markers (AIMs). We used the theory of feature selection from statistical learning in order to obtain AIMsets for BGA inference. Using simulations, we show that this learning procedure works in various cases, and outperforms ad hoc methods, based on statistics like FST or informativeness for the choice of AIMs. Applying our method to data from the 1000 genomes project (excluding Admixed Americans) we identified an AIMset of 12 SNPs, which gives a vanishing misclassification error on a continental scale, as do other published AIMsets. In fact, cross validation shows that there exists a multitude of sets with comparable performance to the optimal AIMset. On a sub-continental scale, we find a set of 55 SNPs for distinguishing the five European populations. The misclassification error is reduced by a factor of two relative to published AIMsets, but is still 30% and therefore too large in order to be useful in forensic applications.

Disassociation of ARID1A with genomic ancestry and prognostic impact in an admixed cohort of Brazilian patients with gastric cancer (GC).

e15585 Background: Loss of expression of ARID1A, a tumor suppressor gene involved in chromatin remodeling and transcription activation, has been associated with worse prognosis in Asian GC patients (Yang et al. 2016). Mutations in ARID1A have been found in 8-27% of GC, usually leading to gene/protein inactivation. Here we evaluated the possible involvement of ARID1A mutations and clinical characteristics, while considering genomic ancestry and survival, in a cohort of Brazilian GC patients. Methods: We included 112 pts diagnosed with GC and treated at AC Camargo Cancer Center before 2013. The study was approved by local IRB. Genomic DNA was used for capture-based enrichment of a customized gene panel including 99 genes. Libraries were sequenced in the NextSeq 500 platform (Illumina), using paired-end reads (2x75bp). For ancestry inference we used a set of ancestry informative markers, covered by target and off-target reads, described by Elhaik et al. (2014). Results: Median age was 64y (37-91), 63% were male, M:F ratio was 1.73. Most cases were classified as Diffuse (47.3%) followed by Intestinal (41.1%), Mixed (2.7%) and 8.9% were deemed unclassifiable by Lauren´s classification. 22.3% were stage I, 20.5% stage II, 42.9% stage III and 14.3% stage IV. 11.6% were in the GEJ and 80.4% were in corpus/antrum. Five patients were EBV positive (4.5%). Genomic ancestry was as follows: 55.4% European, 27.7% Asian, 8.9% African and 8% were highly admixed ( < 50% of any ancestry). ARID1A was mutated in 19% of cases and showed no association with age at diagnosis (p = 0.21), gender (p = 0.76), tumor location (p = 0.55), staging (p = 0.42), Lauren (p = 0.14) or EBV (p = 0.42). ARID1A had no impact on overall survival (OS) (HR 1.17; 95%CI 0.59-2.31; p = 0.6) or disease-free survival (DFS) (HR 1.24; 95%CI 0.66-2.32; p = 0.5), including the subgroup with Asian genomic background: OS-Asia (HR 1.08; 95%CI 0.31-3.81; p = 0.9), DFS-Asia (HR 1.15; 95%CI 0.32-4.12; p = 0.8). Conclusions: ARID1A is a common driver in GC among Brazilian patients. Unlike in Asians, ARID1A was not prognostic in this Brazilian cohort even in the subgroup with a predominant ( > 50%) Asian genomic ancestry.

Survival of gastric cancer (GC) patients is not determined by the predominant genomic ancestry (PGA): Results from an ethnically admixed Brazilian cohort of GC patients.

e15588 Background: Clinical characteristics, treatment response and overall survival of GC patients differ between Asian and non-Asian countries. Here we evaluated the possible associations between PGA, clinical characteristics and survival in an admixed GC Brazilian cohort. Methods: We included 112 GC pts diagnosed and treated at AC Camargo Cancer Center (São Paulo, Brazil) before 2013. The study was approved by local IRB. Genomic DNA was used for capture-based enrichment of a customized gene panel including 99 genes. Libraries were sequenced in the NextSeq 500 platform (Illumina), using paired-end reads (2x75bp). Ancestries were determined through a set of ancestry informative markers (AIMs), covered by target and off-target reads, described by Elhaik et al. (2014). Results: An average of 406 AIMs were recovered from the available samples, revealing average ancestries was as follows: 55.4% European, 27.7% Asian, 8.9% African; 8% of subjects were highly admixed (HA; < 50% of any ancestry). We found no association between PGA and age at diagnosis (p = 0.58), tumor location (p = 0.34), Lauren (p = 0.24) and staging (p = 0.68). There was an association between PGA and gender (p = 0.04) and a marginal association between PGA and EBV (p = 0.056). BRCA2 was the only gene enriched in the Asian subgroup, compared to the other groups combined (p = 0.009). The median follow-up time was 95 months. We found no differences in median overall survival (OS) (p = 0.4) or disease-free survival (DFS) (p = 0.6) according to PGA. The HA subgroup presented worst survival outcomes compared to the other groups aggregated (mOS 34m; 95%CI 5-80 x mOS 71m; 95% CI 44-85, respectively), but the difference was not statistically significant (HR 1,73; 95% CI 0.74-4.05; p = 0.2). Even for patients with > 75% AIMs for any given ancestry, we found no differences in OS between Europeans (n = 25; mOS 86m; 95%CI 80-NA), Asians (n = 22; mOS 83m; 95%CI 51-NA) and Africans (n = 5; mOS 67m; 95%CI 22-NA), p = 0.4. Conclusions: The most prevalent ancestries in this Brazilian GC cohort were European, followed by Asian and African. Although we found associations between ancestry and a few clinical aspects, PGA was not associated with survival.

Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs.

Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner.

Identifying highly informative genetic markers for quantification of ancestry proportions in crossbred sheep populations: implications for choosing optimum levels of admixture

Understanding the relationship between genetic admixture and performances is crucial for the success of crossbreeding programs. Use of small sets of ancestry informative markers (AIMs) is a cost effective option to estimate the levels of admixture in situations where pedigree recording is difficult. In this study we select AIMs from Ovine 50KSNP data (SNP – single nucleotide polymorphism) and validate their ability in estimating the contributions of parental breeds to get information about optimum admixture levels for smallholders. We estimated admixture levels using ADMIXTURE software based on 74 AIMs selected from Ovine 50KSNP data. Awassi x Ethiopian fat-tailed crossbred sheep populations kept in government farms and farmer villages in different districts were included in the study. Mean Awassi levels estimated based on the selected AIMs were close to the Awassi levels obtained from pedigree information. Estimates from the 74 SNPs were compared to subsets of 65, 55, 45, 35, 25 and 15 SNPs selected based on both top and bottom fixation index (FST) rank using Spearman’s rank correlation (r = 0.862–0.996). A t-test comparison revealed that all SNP subsets had produced similar (P > 0.05) estimates with the 74 SNPs, except for the bottom 15 SNPs (P < 0.05). However estimates based on 45 and above SNP subsets were relatively close to the fitted regression line (r = 0.969–0.996). Association of admixture levels with lamb growth showed that Awassi level affected (P < 0.05) eight months weight in both farmer locations, lambs with higher Awassi levels were heavier. Lambing interval of ewes was longer as Awassi level increased, but this drawback was outweighed by the increased productivity of ewes in terms of eight months lamb weight per year. The results indicate that the Ovine 50KSNP array is a powerful tool to identify small sets of AIMs for admixture studies. The results of this study reveal about 45AIMs to accurately estimate admixture levels. If admixture estimation service with such low cost SNP chip would be available, farmers would have a clear market advantage without the need to rely on incomplete or possibly inaccurate pedigree records. Based on the results presented here, we were able to suggest optimum levels of breed composition for the two farmer environments investigated.

Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND).

BackgroundThe presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.ResultsA fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.ConclusionsThe identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.

Leveraging local ancestry to detect gene-gene interactions in genome-wide data.

BackgroundAlthough genome-wide association studies have successfully identified thousands of variants associated to complex traits, these variants only explain a small amount of the entire heritability of the trait. Gene-gene interactions have been proposed as a source to explain a significant percentage of the missing heritability. However, detecting gene-gene interactions has proven to be very difficult due to computational and statistical challenges. The vast number of possible interactions that can be tested induces very stringent multiple hypotheses corrections that limit the power of detection. These issues have been mostly highlighted for the identification of pairwise effects and are even more challenging when addressing higher order interaction effects. In this work we explore the use of local ancestry in recently admixed individuals to find signals of gene-gene interaction on human traits and diseases.ResultsWe introduce statistical methods that leverage the correlation between local ancestry and the hidden unknown causal variants to find distant gene-gene interactions. We show that the power of this test increases with the number of causal variants per locus and the degree of differentiation of these variants between the ancestral populations. Overall, our simulations confirm that local ancestry can be used to detect gene-gene interactions, solving the computational bottleneck. When compared to a single nucleotide polymorphism (SNP)-based interaction screening of the same sample size, the power of our test was lower on all settings we considered. However, accounting for the dramatic increase in sample size that can be achieve when genotyping only a set of ancestry informative markers instead of the whole genome, we observe substantial gain in power in several scenarios.ConclusionLocal ancestry-based interaction tests offer a new path to the detection of gene-gene interaction effects. It would be particularly useful in scenarios where multiple differentiated variants at the interacting loci act in a synergistic manner.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0283-z) contains supplementary material, which is available to authorized users.

Comparison of two online algorithm methods for forensic ancestry inference

The forensic prediction of the biogeographic ancestry based on DNA typing has become more widespread. The search for optimized panels, consisting of a small but efficient and robust set of ancestry informative markers (AIMs), has received increased interest. Several panels published in recent literature would provide excellent information on ancestry as a useful forensic investigative tool. Relying on the genetic profiles from these panels, accurate and efficient estimation of an individual ancestry depends on excellent algorithmic methods. In the present work, a comparison of the FROG-kb (http://frog.med.yale.edu) and Bayesian classification approaches of Snipper (http://mathgene.usc.es/snipper/) was carried out to assess the ability of genetic ancestry inference for the Kidd Lab 55 AISNP panel (Kidd et al., FSI Genetics 2014 (10), 23–32). Preliminary reported data from the online SPSmart browser illustrated that both algorithmic inference methods were adaptable for forensic ancestry assignments of an individual. For a few individuals, especially originating from admixed populations, ancestral assignment was inaccurate or discordant according to the likelihood calculations in FROG-kb or the ratio from Snipper forensic ancestry analysis portal. Therefore, future improvement will require more populations adding into the reference populations for the likelihood function in FROG-kb, as well as appropriate training sets applying to the online Snipper analysis tool.

A minimum set of ancestry informative markers for determining admixture proportions in a mixed American population: the Brazilian set.

The Brazilian population is considered to be highly admixed. The main contributing ancestral populations were European and African, with Amerindians contributing to a lesser extent. The aims of this study were to provide a resource for determining and quantifying individual continental ancestry using the smallest number of SNPs possible, thus allowing for a cost- and time-efficient strategy for genomic ancestry determination. We identified and validated a minimum set of 192 ancestry informative markers (AIMs) for the genetic ancestry determination of Brazilian populations. These markers were selected on the basis of their distribution throughout the human genome, and their capacity of being genotyped on widely available commercial platforms. We analyzed genotyping data from 6487 individuals belonging to three Brazilian cohorts. Estimates of individual admixture using this 192 AIM panels were highly correlated with estimates using ~370 000 genome-wide SNPs: 91%, 92%, and 74% of, respectively, African, European, and Native American ancestry components. Besides that, 192 AIMs are well distributed among populations from these ancestral continents, allowing greater freedom in future studies with this panel regarding the choice of reference populations. We also observed that genetic ancestry inferred by AIMs provides similar association results to the one obtained using ancestry inferred by genomic data (370 K SNPs) in a simple regression model with rs1426654, related to skin pigmentation, genotypes as dependent variable. In conclusion, these markers can be used to identify and accurately quantify ancestry of Latin Americans or US Hispanics/Latino individuals, in particular in the context of fine-mapping strategies that require the quantification of continental ancestry in thousands of individuals.

Translational genomic medicine: common metabolic traits and ancestral components of Mexican Americans

Obesity, type 2 diabetes, hyperlipidaemia, hypertension and liver disease are common metabolic disorders in Mexican Americans, the largest minority population in the US. Mexican Americans are an admixed population with...

Genetic polymorphism and prostate cancer aggressiveness: a case-only study of 1,536 GWAS and candidate SNPs in African-Americans and European-Americans.

Genome-wide association studies have established a number of replicated single nucleotide polymorphisms (SNPs) for susceptibility to prostate cancer (CaP), but it is unclear whether these susceptibility SNPs are also associated with disease aggressiveness. This study evaluates whether such replication SNPs or other candidate SNPs are associated with CaP aggressiveness in African-American (AA) and European-American (EA) men. A 1,536 SNP panel which included 34 genome-wide association study (GWAS) replication SNPs, 38 flanking SNPs, a set of ancestry informative markers, and SNPs in candidate genes and other areas was genotyped in 1,060 AA and 1,087 EA men with incident CaP from the North Carolina-Louisiana Prostate Cancer Project (PCaP). Tests for association were conducted using ordinal logistic regression with a log-additive genotype model and a 3-category CaP aggressiveness variable. Four GWAS replication SNPs (rs2660753, rs13254738, rs10090154, rs2735839) and seven flanking SNPs were associated with CaP aggressiveness (P < 0.05) in three genomic regions: One at 3p12 (EA), seven at 8q24 (5 AA, 2 EA), and three at 19q13 at the kallilkrein-related peptidase 3 (KLK3) locus (two AA, one AA and EA). The KLK3 SNPs also were associated with serum prostate-specific antigen (PSA) levels in AA (P < 0.001) but not in EA. A number of the other SNPs showed some evidence of association but none met study-wide significance levels after adjusting for multiple comparisons. Some replicated GWAS susceptibility SNPs may play a role in CaP aggressiveness. However, like susceptibility, these associations are not consistent between racial groups.

Ancestry Informative Marker Set for Han Chinese Population

The population of Han Chinese is ∼1.226 billion people. Genetic heterogeneity between northern Han Chinese (N-Han) and southern Han Chinese (S-Han) has been demonstrated by recent genome-wide studies. As an initial step toward health disparities and personalized medicine in Chinese population, this study developed a set of ancestry informative markers (AIM) for Han Chinese population.

Interaction between tryptophan hydroxylase I polymorphisms and childhood abuse is associated with increased risk for borderline personality disorder in adulthood

Borderline personality disorder (BPD) is a severe disorder with high morbidity and mortality, but unknown etiology. Childhood abuse has been proposed as an etiological factor, but the mechanism by which an abuse history could influence the risk for BPD has not been determined. The aim of this study was to determine whether the tryptophan hydroxylase 1 (TPH1) gene is related to BPD in a clinical sample, and whether TPH1 genotypes or haplotypes moderate the relationship between abuse history and BPD. Three hundred and ninety-eight patients diagnosed with mood disorders were genotyped for TPH1 G-6526A promoter polymorphism (rs4537731) and the A218C intron 7 polymorphism (rs1800532) and a set of ancestry informative markers, assessed for Diagnostic and Statistical Manual of Mental Disorders, 4th edition diagnoses, and assessed for a history of physical and sexual abuse. Patients with a diagnosis of BPD were more likely to be risk allele carriers (A alleles at both loci) than the non-BPD group. Logistic regression analysis predicting BPD diagnosis with both single-nucleotide polymorphisms and haplotypes showed significant interaction effects between genotype and abuse history. Poisson regression predicting the number of BPD diagnostic criteria met with the same predictor set also included a significant interaction term. Risk allele carriers with a history of abuse had an increased likelihood of a BPD diagnosis. Variation in TPH1 may increase risk for developing BPD as a result of childhood abuse. Elements of BPD pathology may be due in part to a genetically influenced serotonergic dysfunction, which in turn may lead to a differential response to environmental stressors.

Abstract 1868: Evaluation of the nucleotide excision repair polymorphisms for association with lung cancer risk

Abstract There is increasing evidence that decreased nucleotide excision repair (NER) capacity may be associated with increased risk of cancer, including non-small cell lung cancer (NSCLC). We have studied the relationship of the NER pathway gene single nucleotide polymorphisms and haplotypes with NSCLC risk. Using a custom-designed Illumina GoldenGate assay 384 single nucleotide polymorphism (SNP) panel, we have screened for polymorphisms in nucleotide excision repair genes, cell cycle control genes, GSTP1 and ABCB1 and a set of ancestry informative markers in 797 Caucasian incident cases and 992 controls frequency matched for age (range 50-79) and gender. All subjects were ever smokers with a minimum 10 packyear smoking history. Our SNP selection strategy incorporates six SNP classes, i.e. haplotype tagSNPs defined by predicted LD scores; functional SNPs characterized by amino acid substitutions, SNPs that alter protein stability; evolutionary conservation across species; entromics and published epidemiological data. For the estimation of individual SNP and haplotype-specific associations with risk, unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals in a dominant model adjusting for age, gender and packyear. A total of 26 unique SNPs in 14 genes were significantly associated with lung cancer risk. Haplotypes were reconstructed for each gene using HPlus and associations with risk were evaluated using the Cox proportional hazards model. The most frequent haplotype was used as the referent group for the estimation of hazard ratios (HR). Hazard ratios were calculated for common haplotypes i.e. those that were present at a frequency greater than 2% and were adjusted for age, gender and packyears. Among these 14 genes, 7 haplotypes were significant. These data suggest that NER pathway genotypes may serve to define an elevated risk subgroup. Supported in part by NIH 5P50 CA090440. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1868.

Tracing Sub-Structure in the European American Population with PCA-Informative Markers

Genetic structure in the European American population reflects waves of migration and recent gene flow among different populations. This complex structure can introduce bias in genetic association studies. Using Principal Components Analysis (PCA), we analyze the structure of two independent European American datasets (1,521 individuals–307,315 autosomal SNPs). Individual variation lies across a continuum with some individuals showing high degrees of admixture with non-European populations, as demonstrated through joint analysis with HapMap data. The CEPH Europeans only represent a small fraction of the variation encountered in the larger European American datasets we studied. We interpret the first eigenvector of this data as correlated with ancestry, and we apply an algorithm that we have previously described to select PCA-informative markers (PCAIMs) that can reproduce this structure. Importantly, we develop a novel method that can remove redundancy from the selected SNP panels and show that we can effectively remove correlated markers, thus increasing genotyping savings. Only 150–200 PCAIMs suffice to accurately predict fine structure in European American datasets, as identified by PCA. Simulating association studies, we couple our method with a PCA-based stratification correction tool and demonstrate that a small number of PCAIMs can efficiently remove false correlations with almost no loss in power. The structure informative SNPs that we propose are an important resource for genetic association studies of European Americans. Furthermore, our redundancy removal algorithm can be applied on sets of ancestry informative markers selected with any method in order to select the most uncorrelated SNPs, and significantly decreases genotyping costs.