Ancestry-informative Principal Components Research Articles

Exploring the role of HLA variants in neuroblastoma susceptibility through whole exome sequencing.

Although a number of susceptibility loci for neuroblastoma (NB) have been identified by genome-wide association studies, it is still unclear whether variants in the HLA region contribute to NB susceptibility. In this study, we conducted a comprehensive genetic analysis of variants in the HLA region among 724 NB patients and 2863 matched controls from different cohorts. We exploited whole-exome sequencing data to accurately type HLA alleles with an ensemble approach on the results from three different typing tools, and carried out rigorous sample quality control to ensure a fine-scale ancestry matching. The frequencies of common HLA alleles were compared between cases and controls by logistic regression under additive and non-additive models. Population stratification was taken into account adjusting for ancestry-informative principal components. We detected significant HLA associations with NB. In particular, HLA-DQB1*05:02 (OR = 1.61; padj = 5.4 × 10-3) and HLA-DRB1*16:01 (OR = 1.60; padj = 2.3 × 10-2) alleles were associated to higher risk of developing NB. Conditional analysis highlighted the HLA-DQB1*05:02 allele and its residue Ser57 as key to this association. DQB1*05:02 allele was not associated to clinical features worse outcomes in the NB cohort. Nevertheless, a risk score derived from the allelic combinations of five HLA variants showed a substantial predictive value for patient survival (HR = 1.53; p = 0.032) that was independent from established NB prognostic factors. Our study leveraged powerful computational methods to explore WES data and HLA variants and to reveal complex genetic associations. Further studies are needed to validate the mechanisms of these interactions that contribute to the multifaceted pattern of factors underlying the disease initiation and progression.

Abstract 3460: Predicting cessation of immune checkpoint inhibitor therapy due to severe adverse events with an integrated autoimmune disease polygenic risk score

Abstract Background: Immune checkpoint inhibitors (ICIs), including anti-PD1/PD-L1 and anti-CTLA4 agents, have changed the landscape of cancer therapy. However, 6-30% of patients treated with ICIs can develop severe immune-related adverse events (irAEs) depending on the type of therapy used, often leading to cessation of treatment. Hundreds of genetic variants have been associated with autoimmune disorders, and recent genetic studies have developed polygenic risk scores (PRS) for composite risk of autoimmune disease (PRSAID). We used data from an ongoing observational study of patients with non-small cell lung cancer (NSCLC) treated with ICIs to evaluate the association between PRSAID and cessation of ICI therapy due to severe irAEs. Methods: Our cohort comprises 1,316 advanced NSCLC patients who received ICI therapy from four institutions between 2009 and 2022. Genotyping was performed using the Affymetrix Precision Medicine Array, and imputation was performed using 1000 Genomes Reference. To evaluate cessation of therapy due to severe irAEs, we conducted a thorough review of electronic health records. We identified permanent discontinuation of ICIs due to irAEs as cessation for at least 6 months without any disease progression. We tested the association of a previously published PRSAID (PMID: 35393596) with cessation of ICI due to any severe irAE. PRSAID was converted to a standard normal distribution. We conducted an unconditional logistic regression model to evaluate the association between a standardized PRSAID and discontinuation of ICI therapy due to severe irAEs. All models were adjusted for age at diagnosis, sex, type of ICI therapy, recruitment site, and 5 ancestry-informative principal components. Results: Of the 1,316 participants with genotype and outcome data, 171 (13.5%) of patients stopped ICI therapy due to severe irAEs. The most common irAEs leading to discontinuation were colitis, hepatitis, and pneumonitis. The PRSAID predicts the cessation of therapy due to severe irAEs with an odds ratio (OR) per standard deviation (SD) of 1.20 (95% confidence intervals [CI]=1.02-1.41, p=0.03). The association was stronger in individuals with high genetic risk (top 25th percentile compared to bottom 75th percentile of the PRSAID) (OR=1.60, 95% CI = 1.11-2.28, p=0.01). When we stratified the analysis by therapy type, we found an OR of 1.17 (95% CI-0.98-1.39, p = 0.08) for the anti-PD1/PD-L1 monotherapy groups and an OR of 1.48 (95% CI=0.94-2.40,p=0.09) for the dual anti-PD1/PD-L1 and anti-CTLA4 therapy group. Conclusions: An integrated PRS for autoimmunity can predict the cessation of ICI therapy due to severe irAEs in patients with advanced cancer. These findings suggest that PRS may help determine which patients may benefit from careful monitoring or even preventative measures for irAEs during ICI therapy. Citation Format: Pooja Middha, Rohit Thummalapalli, Zoe Quandt, Princess Margaret Lung Group, Matthew A. Gubens, Christine M. Lovly, Geoffrey Liu, Melinda C. Aldrich, Adam J. Schoenfeld, Elad Ziv. Predicting cessation of immune checkpoint inhibitor therapy due to severe adverse events with an integrated autoimmune disease polygenic risk score [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3460.

Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia.

Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.

SA114 - GENETIC ETIOLOGY OF SELF-RATING OF THE EFFECTS OF ALCOHOL (SRE) SCORES IN YOUNG ADULTS

Background Alcohol misuse is a significant public health concern with social, medical, and economic consequences. Previous studies suggest that initial sensitivity to alcohol may impact use of the substance: those with low sensitivity may drink more, potentially establishing unhealthy drinking habits that persist into adulthood. The Self-Rating of the Effects of Alcohol (SRE) scale was developed to quantify initial sensitivity to alcohol, and SRE scores have been positively associated with concurrent and later drinking behaviors. Furthermore, evidence suggests that SRE scores are influenced by familial factors, raising the possibility that genetic liability to low alcohol sensitivity may increase risk of later alcohol misuse. We sought to clarify the role of genetic factors on SRE scores in two samples of young adults. Methods We derived SRE scores in two population-based cohort studies. ALSPAC participants were born between 1991–1992 in the southwest region of England and have been assessed at least once per year since birth. SRE scores were derived based on assessments at ages 15.5, 16.5, and 17.5. S4S participants were students at a large, public, urban university in the southeastern US, enrolled during the fall or spring of their freshman year (2011–2013), and assessed each subsequent spring. Participants were of diverse ancestry and were 18+ years of age at initial enrollment. The first available SRE score was used for subsequent analyses. Phenotypic and genotypic data meeting all quality control filters were available for a total of N=7339 participants. We conducted Genome-Wide Association Studies (GWAS) within each sample/ancestry group, using ancestry-informative principal components, sex, and age at first available SRE assessment as covariates. Initial GWAS results were meta-analyzed in METAL. SNP-based heritabilities for each sample/ancestry group were estimated in GCTA. Additional secondary analyses were conducted in VEGAS and JEPEGMIX2. Results A total of 15,642,250 markers were analyzed in at least one group. No individual marker met genome-wide significance criteria. The top marker, rs146298733 (p=3.16e-07), mapped to an intron in DLGAP1, variants in which have been previously associated with psychiatric outcomes including major depression and obsessive-compulsive disorder. Meta-analysis of GCTA results indicated that SRE is modestly heritable (h2SNP=0.19, SE=0.10), though this was driven primarily by the ALSPAC sample, for which assessments were prospective. Pathway analyses implicated the GABAergic system and genes related to thromboxane signaling, both of which have been associated with alcohol-related phenotypes. Discussion We present evidence consistent with prior reports that initial sensitivity to alcohol is influenced by genetic factors. Preliminary analyses implicate systems known to influence other alcohol phenotypes and provide novel targets for future analysis. Implicated loci and aggregate genetic risk should be confirmed in independent samples. Heterogeneity across samples suggests that assessment methods are important to SRE measurement, which may have implications for genetic analyses. Further characterization of genetic influences may elucidate mechanisms underlying the pathway from initial sensitivity to alcohol problems.

Two HLA Class II Gene Variants Are Independently Associated with Pediatric Osteosarcoma Risk.

Background: The genetic etiology of osteosarcoma remains poorly understood despite the publication of a genome-wide association study. Association between HLA genetic variants and risk of several cancers has been observed, but HLA variation is not well captured by standard SNP arrays.Methods: We genotyped 207 Californian pediatric osteosarcoma cases and 696 controls of European ancestry using a custom genome-wide array supplemented with approximately 6,000 additional probes across the MHC region. We subsequently imputed 4-digit classical HLA alleles using a reference panel of 5,225 individuals who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for ancestry-informative principal components, and top associations from the discovery analysis underwent replication in an independent dataset of 657 cases and 1,183 controls.Results: Three highly correlated HLA class II variants (r 2 = 0.33-0.98) were associated with osteosarcoma risk in discovery analyses, including HLA-DRB1*0301 (OR = 0.52; P = 3.2 × 10-3), HLA-DQA1*0501 (OR = 0.74; P = 0.031), and HLA-DQB1*0201 (OR = 0.51; P = 2.7 × 10-3). Similar associations were observed in the replication data (P range = 0.011-0.037). Meta-analysis of the two datasets identified HLA-DRB1*0301 as the most significantly associated variant (ORmeta = 0.62; P meta = 1.5 × 10-4), reaching Bonferroni-corrected statistical significance. The meta-analysis also revealed a second significant independent signal at HLA-DQA1*01:01 (ORmeta = 1.33, P meta = 1.2 × 10-3), and a third suggestive association at HLA-DQB1*0302 (ORmeta = 0.73, P meta = 6.4 × 10-3).Conclusions: Multiple independent HLA class II alleles may influence osteosarcoma risk.Impact: Additional work is needed to extend our observations to other patient populations and to clarify the potential causal mechanisms underlying these associations. Understanding immunologic contributions to the etiology of osteosarcoma may inform rational therapeutic targets. Cancer Epidemiol Biomarkers Prev; 27(10); 1151-8. ©2018 AACR.

Abstract 228: Association analysis across different populations identifies 26 new cutaneous melanoma risk loci

Abstract Heritability of cutaneous melanoma is among the highest across cancer types and is mostly determined by common, noncoding genetic variants. Previous genome-wide association studies (GWAS), mostly including subjects from Australia and Northern European countries, had identified twenty genetic loci associated with melanoma risk. To characterize the genetic landscape of cutaneous melanoma across different populations, we conducted a new association study in Southern European countries including 6,043 melanoma cases and 10,383 controls from the MelaNostrum Consortium. Moreover, we largely expanded the analyses of melanoma cases and controls from other populations, for a total of 27,450 histologically confirmed melanoma cases and 49,888 controls from Northern Europe, Southern Europe, USA and Australia. Imputation was done using the Haplotype Reference Consortium as a reference panel. We assessed the association between cutaneous melanoma risk and single-nucleotide polymorphisms (SNPs) adjusting for country and ancestry-informative principal components. We identified 26 new genetic loci associated with melanoma risk achieving genome-wide significance. The pigmentation pathway, with TYRP1 and MITF, and the telomere-related pathway with RTEL1, TERC, and POT1 among the candidate genes, continued to show an important role for melanoma susceptibility. Additional candidate pathways emerged, including signaling (with GPRC5A and DOCK8), cell-cell junction (with CDH1), immune-related functions (with DCST2, involved in antigen processing), transcriptional regulation (with FOXD3, which represses MITF expression), or tumor-suppressor genes (TP53). Adding genotype data from 6,130 self-reported melanoma cases in a sensitivity analysis identified eight additional novel genetic loci involved in the HLA region, signaling transduction and transcription factor functions. A combined analysis of the melanoma GWAS with the GWAS of pigmentation characteristics from the UK Biobank including 500,000 UK persons, and with a GWAS of nevus density including over 52,000 persons, revealed substantial overlap across phenotypes. Although the effect size of the SNPs on melanoma risk was consistent across populations, substantial differences in minor allele frequency (MAF) were observed in pigmentation-related genes between Northern and Southern European populations; for example, MC1R, SLC45A2, and ASIP SNP MAF was 8.2, 3.1 and 14.2 in Northern and 2.6, 8.8, and 5.5 in Southern European subjects, respectively. Additional analyses based on melanoma histologic subtypes and body site distribution are ongoing. These results provide further insight into genetic susceptibility to cutaneous melanoma and provide the opportunity for genetic risk scores in risk-prediction models for early detection and targeted prevention of the disease. Citation Format: Cristina Pellegrini, Matthew Law, Mark Iles, Mitch Machiela, Alex Stratigos, Tongwu Zhang, Kevin Brown, Julia Newton-Bishop, Nick Hayward, Nick Martin, Alisa Goldstein, Rose Yang, Stephen Chanock, Florence Demenais, Susana Puig, Eduardo Nagore, Jianxin Shi, Tim Bishop, Stuart McGregor, Maria Teresa Landi, GenoMEL Consortium, MelaNostrum Consortium. Association analysis across different populations identifies 26 new cutaneous melanoma risk loci [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 228.

Candidate gene analysis in the São Paulo Epidemiologic Sleep Study (EPISONO) shows an association of variant in PDE4D and sleepiness

IntroductionSleepiness and cardiovascular disease share common molecular pathways; thus, genetic risk factors for sleepiness may also predict cardiovascular disease risk. This study explored the associations between subjective sleepiness and single-nucleotide polymorphisms (SNPs) in candidate genes within oxidative stress, inflammatory, and neuronal pathways, which may contribute to sleepiness and downstream cardiovascular disease risk: Cytochrome B-245, Alpha Polypeptide (CYBA), Cytochrome B-245, Beta Polypeptide (CYBB), Neutrophil Cytosolic Factor (NCF2), Tumor Necrosis Factor-Alpha (TNFA), and Phosphodiesterase 4D (PDE4D). MethodsAdults (N = 918) from the general population who were a part of the São Paulo Epidemiologic Sleep Study (EPISONO) in São Paulo, Brazil, were genotyped using Human Omni Express BeadChip array. The average age was 42 ± 14.5 years, subjects had a mean body mass index (BMI) of 26.9 ± 5.4 kg/m2, and 44% were male. Based on the Epworth Sleepiness Scale (ESS), subjects were classified as having sleepiness (ESS ≥ 10) or no sleepiness (ESS < 10). Logistic regression models were used to examine the associations with SNPs within candidate genes and sleepiness, adjusting for age, gender, BMI, Apnea–Hypopnea Index (AHI), total sleep time, and ancestry informative principal components (PCs). Complementary analyses using linear regression to assess the relationship between SNPs and continuous ESS were performed. ResultsWe observed a novel association between the C allele of the rs12522161 SNP on PDE4D and a decreased likelihood of sleepiness, controlling for covariates and ancestry [OR (95% CI) = 0.64 (0.50, 0.81); p = 0.0002]. ConclusionWe present data for a novel genetic association with sleepiness for an SNP on the PDE4D gene, rs12522161.

Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma.

Although genome-wide association studies have identified several susceptibility loci for adult glioma, little is known regarding the potential contribution of genetic variation in the human leukocyte antigen (HLA) region to glioma risk. HLA associations have been reported for various malignancies, with many studies investigating selected candidate HLA polymorphisms. However, no systematic analysis has been conducted in glioma patients, and no investigation into potential non-additive effects has been described. We conducted comprehensive genetic analyses of HLA variants among 1746 adult glioma patients and 2312 controls of European-ancestry from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, and we imputed HLA alleles using a reference panel of 5225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the HLA region are linked, we created multigene haplotypes consisting of the genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, inclusion of a dominance term significantly improved the model for multigene haplotype HLA-DRB1*1501-DQA1*0102-DQB1*0602 (P = 0.002). Heterozygous carriers of the haplotype had an increased risk of glioma [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.01-1.49], while homozygous carriers were at decreased risk compared with non-carriers (OR 0.64; 95% CI 0.40-1.01). Our results suggest that the DRB1*1501-DQA1*0102-DQB1*0602 haplotype may contribute to the risk of glioma in a non-additive manner, with the positive dominance effect partly explained by an epistatic interaction with HLA-DRB1*0401-DQA1*0301-DQB1*0301.

Abstract 1320: Non-additive and interaction effects of HLA class 2 polymorphism contributing to risk of glioma

Abstract Although genome-wide association studies have identified a number of susceptibility loci for adult glioma, little is still known regarding whether polymorphisms in the human leukocyte antigen (HLA) region contribute risk. HLA associations have previously been reported for a number of malignancies, with selected HLA polymorphisms investigated in a subset of glioma studies. However, no systematic analysis has been conducted to date, and no investigation into potential non-additive effects of such associations has been described. In this study, we conducted comprehensive genetic analyses of HLA variants in the major histocompatibility complex (MHC) region among 1,746 adult glioma patients and 2,312 controls from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, containing 1,822 SNP probes across the MHC region. We imputed HLA alleles using a reference panel of 5,225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Subjects were of European-ancestry, and case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the MHC region are linked, we created multi-locus haplotypes consisting of genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, DRB1*15:01-DQA1*01:02-DQB1*06:02 showed an improvement in model fit after the inclusion of a non-additive term, which was significant after Bonferroni correction (P = 2.5x10-3). Furthermore, the interaction of DRB1*15:01-DQA1*01:02-DQB1*06:02 with haplotype DRB1*04:01-DQA1*03:01- DQB1*03:01 resulted in a 3.80-fold increase in the odds of glioma (P = 8.8x10-3). Our results indicate that the DRB1*15:01-DQA1*01:02-DQB1*06:02 haplotype contributes to the risk of glioma via a dominant effect, with heterozygosity conferring greater risk of glioma than expected from homozygote disease risk in an additive model. Citation Format: Chenan Zhang, Kyle Walsh. Non-additive and interaction effects of HLA class 2 polymorphism contributing to risk of glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1320. doi:10.1158/1538-7445.AM2017-1320

Genetic and environmental risk factors for rheumatoid arthritis in a UK African ancestry population: the GENRA case-control study.

Objectives. To evaluate whether genetic and environmental factors associated with RA in European and Asian ancestry populations are also associated with RA in African ancestry individuals. Methods. A case–control study was undertaken in 197 RA cases and 868 controls of African ancestry (Black African, Black Caribbean or Black British ethnicity) from South London. Smoking and alcohol consumption data at RA diagnosis was captured. Genotyping was undertaken (Multi-Ethnic Genotyping Array) and human leukocyte antigen (HLA) alleles imputed. The following European/Asian RA susceptibility factors were tested: 99 genome-wide loci combined into a genetic risk score; HLA region [20 haplotypes; shared epitope (SE)]; smoking; and alcohol consumption. The SE was tested for its association with radiological erosions. Logistic regression models were used, including ancestry-informative principal components, to control for admixture. Results. European/Asian susceptibility loci were associated with RA in African ancestry individuals. The genetic risk score provided an odds ratio (OR) for RA of 1.53 (95% CI: 1.31, 1.79; P = 1.3 × 10 −7). HLA haplotype ORs in European and African ancestry individuals were highly correlated (r = 0.83, 95% CI: 0.56, 0.94; P = 1.1 × 10 −4). Ever-smoking increased (OR = 2.36, 95% CI: 1.46, 3.82; P = 4.6 × 10 −4) and drinking alcohol reduced (OR = 0.34, 95% CI: 0.20, 0.56; P = 2.7 × 10 −5) RA risk in African ancestry individuals. The SE was associated with erosions (OR = 2.61, 95% CI: 1.36, 5.01; P = 3.9 × 10 −3). Conclusion. Gene–environment RA risk factors identified in European/Asian ancestry populations are relevant in African ancestry individuals. As modern statistical methods facilitate analysing ancestrally diverse populations, future genetic studies should incorporate African ancestry individuals to ensure their implications for precision medicine are universally applicable.

T20 - New Insights Into The Pharmacogenomics Of Antidepressant Response From The Gendep And Star*D Studies: Results Of Rare Variant Analysis And High-Density Imputation

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons are limited coverage of genetic variants, phenotypic heterogeneity and small sample size. This study investigated the genetic predictors of antidepressant efficacy in Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) samples trying to address some of the reported limitations. In detail: 1) coverage of genetic variants was increased by adding exome array data to previously available genome-wide data and by genotype imputation using the largest available reference panel (Haplotype Reference Consortium (HRC)); 2) a meta-analysis was performed using SNP methods and multi-marker tests at gene and pathway level. Each dataset was imputed using Minimac3 and the HRC panel after standard quality control. Both samples included patients with diagnosis of major depressive disorder. In GENDEP, patients were partially randomized to escitalopram or nortriptyline; STAR*D patients were treated with citalopram. Escitalopram is the active isomer of citalopram, thus the whole GENDEP sample and the escitalopram-treated subgroup were meta-analyzed with STAR*D. The phenotypes were depressive symptom improvement and remission at week 12 according to standard scales. SNP-level analysis was performed using PLINK (pngu.mgh.harvard.edu/~purcell/plink/); gene and pathway analyses were performed using MAGMA (http://ctglab.nl/software/magma). Covariates were age, baseline severity, center of recruitment and ancestry-informative principal components. NEWMEDS (http://www.newmeds-europe.com) consortium samples, excluding GENDEP, served for replication. 7,062,950 SNPs were analysed in GENDEP (n=738) and STAR*D (n=1409). There was no evidence of genomic inflation (lambda values were ≤ 1.01). No SNP was associated with symptom improvement or remission in the full meta-analysis. In the citalopram/escitalopram analysis, rs116692768 (MAF=0.033, p=1.87e-08, ITGA9 or integrin alpha 9 gene) and rs76191705 (MAF=0.012, p=2.39e-08, NRXN3 or neurexin 3 gene) were associated with symptom improvement. At gene level (whole sample), OR4K2 was associated with improvement (corrected p=0.04), but its effect was inconsistent between the samples. At pathway level (whole sample), the Gene Ontology terms GO:0005694 (chromosome) and GO:0044427 (chromosomal part) were associated with improvement (corrected p=0.007 and 0.045, respectively). Genome-wide significant SNPs were not replicated in NEWMEDS SSRI-treated sample (n=751) (p>0.05). ITGA9 and NRXN3 show a meaningful biological rationale for being involved in antidepressant effect. ITGA9 codes for a membrane glycoprotein receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in post-synaptic and pre-synaptic differentiation, with relevant implications for synaptic activity and synaptic plasticity. Interestingly, rs76191705 is a non-sense mediated decay transcript variant and a polymorphism in complete LD with it (rs79302561) acts as an enhancer of gene expression (Ensembl GRCh37 release 84). However, no convincing replication of these findings was achieved and further studies may be useful to clarify the role of these genes in antidepressant efficacy.

Educational attainment influences levels of homozygosity through migration and assortative mating.

Individuals with a higher education are more likely to migrate, increasing the chance of meeting a spouse with a different ancestral background. In this context, the presence of strong educational assortment can result in greater ancestry differences within more educated spouse pairs, while less educated individuals are more likely to mate with someone with whom they share more ancestry. We examined the association between educational attainment and F roh (= the proportion of the genome consisting of runs of homozygosity [ROHs]) in ~2,000 subjects of Dutch ancestry. The subjects’ own educational attainment showed a nominally significant negative association with F roh (p = .045), while the contribution of parental education to offspring F roh was highly significant (father: p < 10-5; mother: p = 9×10-5), with more educated parents having offspring with fewer ROHs. This association was significantly and fully mediated by the physical distance between parental birthplaces (paternal education: p mediation = 2.4 × 10-4; maternal education: p mediation = 2.3 × 10-4), which itself was also significantly associated with F roh (p = 9 × 10-5). Ancestry-informative principal components from the offspring showed a significantly decreasing association with geography as parental education increased, consistent with the significantly higher migration rates among more educated parents. Parental education also showed a high spouse correlation (Spearman’s ρ = .66, p = 3 × 10-262). We show that less educated parents are less likely to mate with the more mobile parents with a higher education, creating systematic differences in homozygosity due to ancestry differences not directly captured by ancestry-informative principal components (PCs). Understanding how behaviors influence the genomic structure of a population is highly valuable for studies on the genetic etiology of behavioral, cognitive, and social traits.

Association Between Autozygosity and Major Depression: Stratification Due to Religious Assortment

The effects of inbreeding on the health of offspring can be studied by measuring genome-wide autozygosity as the proportion of the genome in runs of homozygosity (F roh) and relate F roh to outcomes such as psychiatric phenotypes. To successfully conduct these studies, the main patterns of variation for genome-wide autozygosity between and within populations should be well understood and accounted for. Within population variation was investigated in the Dutch population by comparing autozygosity between religious and non-religious groups. The Netherlands have a history of societal segregation and assortment based on religious affiliation, which may have increased parental relatedness within religious groups. Religion has been associated with several psychiatric phenotypes, such as major depressive disorder (MDD). We investigated whether there is an association between autozygosity and MDD, and the extent to which this association can be explained by religious affiliation. All F roh analyses included adjustment for ancestry-informative principal components (PCs) and geographic factors. Religious affiliation was significantly associated with autozygosity, showing that F roh has the ability to capture within population differences that are not captured by ancestry-informative PCs or geographic factors. The non-religious group had significantly lower F roh values and significantly more MDD cases, leading to a nominally significant negative association between autozygosity and depression. After accounting for religious affiliation, MDD was not associated with F roh, indicating that the relation between MDD and inbreeding was due to stratification. This study shows how past religious assortment and recent secularization can have genetic consequences in a relatively small country. This warrants accounting for the historical social context and its effects on genetic variation in association studies on psychiatric and other related traits.

Choice of population structure informative principal components for adjustment in a case-control study

BackgroundThere are many ways to perform adjustment for population structure. It remains unclear what the optimal approach is and whether the optimal approach varies by the type of samples and substructure present. The simplest and most straightforward approach is to adjust for the continuous principal components (PCs) that capture ancestry. Through simulation, we explored the issue of which ancestry informative PCs should be adjusted for in an association model to control for the confounding nature of population structure while maintaining maximum power. A thorough examination of selecting PCs for adjustment in a case-control study across the possible structure scenarios that could occur in a genome-wide association study has not been previously reported.ResultsWe found that when the SNP and phenotype frequencies do not vary over the sub-populations, all methods of selection provided similar power and appropriate Type I error for association. When the SNP is not structured and the phenotype has large structure, then selection methods that do not select PCs for inclusion as covariates generally provide the most power. When there is a structured SNP and a non-structured phenotype, selection methods that include PCs in the model have greater power. When both the SNP and the phenotype are structured, all methods of selection have similar power.ConclusionsStandard practice is to include a fixed number of PCs in genome-wide association studies. Based on our findings, we conclude that if power is not a concern, then selecting the same set of top PCs for adjustment for all SNPs in logistic regression is a strategy that achieves appropriate Type I error. However, standard practice is not optimal in all scenarios and to optimize power for structured SNPs in the presence of unstructured phenotypes, PCs that are associated with the tested SNP should be included in the logistic model.

No association of the serotonin transporter polymorphisms 5‐HTTLPR and RS25531 with schizophrenia or neurocognition

A promoter polymorphism in the serotonin transporter gene has been widely studied in neuropsychiatry. We genotyped the 5-HTTLPR/rs25531 triallelic polymorphism in 728 schizophrenia cases from the CATIE study and 724 control subjects. In a logistic regression with case/control status as dependent variable and 7 ancestry-informative principal components as covariates, the effect of 5-HTTLPR/rs25531 composite genotype was not significant (odds ratio = 1.008, 95% CI 0.868-1.172, P = 0.91). In cases only, 5-HTTLPR/rs25531 was not associated with neurocognition (summary neurocognitive index P = 0.21, working memory P = 0.32) or symptomatology (PANSS positive P = 0.67 and negative symptoms P = 0.46). We were unable to identify association of the triallelic 5-HTTLPR with schizophrenia, neurocognition, or core psychotic symptoms even at levels of significance unadjusted for multiple comparisons.

Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies.

We report a genome-wide association study (GWAS) of major depressive disorder (MDD) in 1,221 cases from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and 1,636 screened controls. No genome-wide evidence for association was detected. We also carried out a meta-analysis of three European-ancestry MDD GWAS datasets: STAR*D, Genetics of Recurrent Early-Onset Depression (GenRED) and the publicly-available Genetic Association Information Network MDD dataset (GAIN-MDD). These datasets, totaling 3,957 cases and 3,428 controls, were genotyped using four different platforms (Affymetrix 6.0, 5.0 and 500K, and Perlegen). For each of 2.4 million HapMap II SNPs, using genotyped data where available and imputed data otherwise, single-SNP association tests were carried out in each sample with correction for ancestry-informative principal components. The strongest evidence for association in the meta-analysis was observed for intronic SNPs in ATP6V1B2 (P = 6.78 × 10−7), SP4 (P = 7.68 × 10−7) and GRM7 (P = 1.11 × 10−6). Additional exploratory analyses were carried out for a narrower phenotype (recurrent MDD with onset before age 31, N = 2,191 cases), and separately for males and females. Several of the best findings were supported primarily by evidence from narrow cases or from either males or females. Based on previous biological evidence, we consider GRM7 a strong MDD candidate gene. Larger samples will be required to determine whether any common SNPs are significantly associated with MDD.