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Traditional statistical methods for confidentiality protection of statistical databases do not scale well to deal with GWAS databases especially in terms of guarantees regarding protection from linkage to external information. The more recent concept of differential privacy, introduced by the cryptographic community, is an approach which provides a rigorous definition of privacy with meaningful privacy guarantees in the presence of arbitrary external information, although the guarantees may come at a serious price in terms of data utility. Building on such notions, we propose new methods to release aggregate GWAS data without compromising an individual's privacy. We present methods for releasing differentially private minor allele frequencies, chi-square statistics and p-values. We compare these approaches on simulated data and on a GWAS study of canine hair length involving 685 dogs. We also propose a privacy-preserving method for finding genome-wide associations based on a differentially-private approach to penalized logistic regression.

AbstractSelf-rated health questions have been proven to be a highly reliable and valid measure of overall health as measured by other indicators in many population groups. It also has been shown to be a very good predictor of mortality, chronic or severe diseases, and the need for services, and is positively correlated with clinical assessments. Genetic factors have been estimated to account for 25–64% of the variance in the liability of self-rated health. The aim of the present study was to identify Single Nucleotide Polymorphisms (SNPs) underlying the heritability of self-rated health by conducting a genome-wide association analysis in a large sample of 6,706 Australian individuals aged 18–92. No genome wide significant SNPs associated with self-rated health could be identified, indicating that self-rated health may be influenced by a large number of SNPs with very small effect size. A very large sample will be needed to identify these SNPs.

Genetic technologies used in breeding of small ruminants requires searching for new molecular markers of productive traits. The most effective for this is genome-wide association study (GWAS) of single nucleotide polymorphisms (SNP) with economically valuable traits. The paper presents results of study of associations of the frequency of single nucleotide polymorphisms with a rank assessment according to complex of productive traits (super-elite) in Romanov sheep using DNA biochips Ovine Infinium HD BeadChip 600K. Eleven SNPs have been found having significant correlation with the animals belonging to the "super-elite" group. Five substitutions are located in the genes introns, six are related to intergenic polymorphisms. The highest reliability of association with productivity was observed in substitution rs410516628 (р = 3,14 · 10-9) located on the 3rd chromosome. Substitution rs422028000 on 2nd chromosome differs with the fact that in the "super-elite" group it was found in 90 % of haplotypes. Polymorphisms rs411162754 (1st chromosome) and rs417281100 (10th chromosome) in our study turned out to be the rarest – only in "super-elite" group and only in a quarter of haplotypes. The genes located near the identified SNPs are mainly associated with metabolic and regulatory processes. Our study has identified several new candidate genes with polymorphism probably associated with the ranking in terms of productivity in Romanov sheep: LTBP1, KCNH8, LMX1B, ZBTB43, MSRA, CHPF, PID1 and DNER. The results obtained create a theoretical basis for further study of candidate genes affecting implementation of phenotypic traits in Romanov sheep. The revealed polymorphisms associated with the productive traits of sheep can be used in practical breeding as molecular and genetic markers for selection of parental pairs.

Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small-effect variants.

As part of the Genes, Environment and Development Initiative, the Minnesota Center for Twin and Family Research (MCTFR) undertook a genome-wide association study, which we describe here. A total of 8,405 research participants, clustered in four-member families, have been successfully genotyped on 527,829 single nucleotide polymorphism (SNP) markers using Illumina's Human660W-Quad array. Quality control screening of samples and markers as well as SNP imputation procedures are described. We also describe methods for ancestry control and how the familial clustering of the MCTFR sample can be accounted for in the analysis using a Rapid Feasible Generalized Least Squares algorithm. The rich longitudinal MCTFR assessments provide numerous opportunities for collaboration.

Breastfeeding has been an important survival trait during human history, though it has long been recognized that individuals differ in their exact breastfeeding behavior. Here our aims were, first, to explore to what extent genetic and environmental influences contributed to the individual differences in breastfeeding behavior; second, to detect possible genetic variants related to breastfeeding; and lastly, to test if the genetic variants associated with breastfeeding have been previously found to be related with breast size. Data were collected from a large community-based cohort of Australian twins, with 3,364 women participating in the twin modelling analyses and 1,521 of them included in the genome-wide association study (GWAS). Monozygotic (MZ) twin correlations (rMZ = 0.52, 95% CI 0.46–0.57) were larger than dizygotic (DZ) twin correlations (rDZ = 0.35, 95% CI 0.25–0.43) and the best-fitting model was the one composed by additive genetics and unique environmental factors, explaining 53% and 47% of the variance in breastfeeding behavior, respectively. No breastfeeding-related genetic variants reached genome-wide significance. The polygenic risk score analyses showed no significant results, suggesting breast size does not influence breastfeeding. This study confers a replication of a previous one exploring the sources of variance of breastfeeding and, to our knowledge, is the first one to conduct a GWAS on breastfeeding and look at the overlap with variants for breast size.

Abstract
Soybean is increasingly becoming one of the main oilseeds crops in Kazakhstan, with a major growing area in the south-eastern part of the country. The comparative assessment of small-size (108) and medium-size (276 accessions) collections of soybean originated from five regions of the world was made in field trials in Almaty region (south-east of Kazakhstan). The full collection was genotyped using the Illumina iSelect 6K SNP (single nucleotide polymorphism) array that allowed observation of 4651 polymorphic SNPs. The genome-wide association study (GWAS) was conducted using the following six important agronomic traits: flowering time, seed maturation time, plant height, number of fertile nodes, number of seeds per node, and thousand seed weight. In total, GWAS using TASSEL package identified 56 stable QTNs (quantitative trait nucleotdies) for all the studied traits, including 42 QTNs detected using the medium-size collection. It was shown that the medium-size population, in comparison with the small-size population, was preferable for the detection of significant associations. A comparative analysis of the data with previously published results suggested that 36 of the stable 56 QTNs were presumably novel associations. The revealed QTNs can be used in the molecular breeding projects for soybean yield improvement.

Mexican Americans (MAs) and American Indians (AIs) constitute conspicuously understudied groups with respect to risk for post-traumatic stress disorder (PTSD), especially in light of findings showing racial/ethnic differences in trauma exposure and risk for PTSD. The purpose of this study was to examine genetic influences on PTSD in two minority cohorts. A genome-wide association study (GWAS) with sum PTSD symptoms for trauma-exposed subjects was run in each cohort. Six highly correlated variants in olfactory receptor family 11 subfamily L member 1 (OR11L1) were suggestively associated with PTSD in the MA cohort. These associations remained suggestively significant after permutation testing. A signal in a nearby olfactory receptor on chromosome 1, olfactory receptor family 2 subfamily L member 13 (OR2L13), tagged by rs151319968, was nominally associated with PTSD in the AI sample. Although no variants were significantly associated after correction for multiple testing in a meta-analysis of the two cohorts, pathway analysis of the top hits showed an enrichment cluster of terms related to sensory transduction, olfactory receptor activity, G-protein coupled receptors, and membrane. As previous studies have proposed a role for olfaction in PTSD, our results indicate this influence may be partially driven by genetic variation in the olfactory system.

AbstractHuman height and body mass index are influenced by a large number of genes, each with small effects, along with environment. To identify common genetic variants associated with these traits, we performed genome-wide association studies in 11,536 individuals composed of Australian twins, family members, and unrelated individuals at ∼550,000 genotyped SNPs. We identified a single genome-wide significant variant for height (Pvalue = 1.06 × 10–9) located inHHIP, a well-replicated height-associated gene. Suggestive levels of association were found for other known genes associated with height (Pvalues < 1 × 10–6):ADAMTSL3,EFEMP1,GPR126, andHMGA2; and BMI (Pvalues < 1 × 10–4):FTOandMC4R. Together, these variants explain less than 2% of total phenotypic variation for height and 0.5% for BMI.

Genome-wide association studies (GWAS) of attention-deficit/hyperactivity disorder (ADHD) offer the benefit of a hypothesis-free approach to measuring the quantitative effect of genetic variants on affection status. Generally the findings of GWAS relying on ADHD status have been non-significant, but the one study using quantitative measures of symptoms found SLC9A9 and SLC6A1 were associated with inattention and hyperactivity–impulsivity. Accordingly, we performed a GWAS using quantitative measures of each ADHD subtype measured with the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) scale in two community-based samples. This scale captures the full range of attention and kinetic behavior; from high levels of attention and appropriate activity to the inattention and hyperactivity–impulsivity associated with ADHD within two community-based samples. Our discovery sample comprised 1,851 participants (mean age = 22.8 years [4.8]; 50.6% female), while our replication sample comprised 155 participants (mean age = 26.3 years [3.1]; 68.4% females). Age, sex, age × sex, and age2 were included as covariates and the results from each sample were combined using meta-analysis, then analyzed with a gene-based test to estimate the combined effect of markers within genes. We compare our results with markers that have previously been found to have a strong association with ADHD symptoms. Neither the GWAS nor subsequent meta-analyses yielded genome-wide significant results; the strongest effect was observed at rs2110267 (4.62 × 10−7) for symptoms of hyperactivity–impulsivity. The strongest effect in the gene-based test was for GPR139 on symptoms of inattention (6.40 × 10−5). Replication of this study with larger samples will add to our understanding of the genetic etiology of ADHD.

AbstractPrevious genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10–09; observational measure lead SNP rs11803731, p = 2.1 × 10–17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.

Genome-wide association studies and biobanks are at the forefront of genomics research and possess unprecedented potential to improve public health. However, for public health genomics to ultimately fulfill its potential, technological and scientific advances alone are insufficient. Scientists, ethicists, policy makers, and regulators must work closely together with research participants and communities in order to craft an equitable and just ethical framework, and a sustainable environment for effective policies. Such a framework should be a 'hybrid' form which balances equity and solidarity with entrepreneurship and scientific advances. A good balance between research and policy on one hand, and privacy, protection and trust on the other is the key for public health improvement based on advances in genomics science.