Bivariate Genome-wide Association Study Research Articles

A genetic correlation and bivariate genome-wide association study of grip strength and depression.

Grip strength is an important biomarker reflecting muscle strength, and depression is a psychiatric disorder all over the world. Several studies found a significant inverse association between grip strength and depression, and there is also evidence for common physiological mechanisms between them. We used twin data from Qingdao, China to calculate genetic correlations, and we performed a bivariate GWAS to explore potential SNPs, genes, and pathways in common between grip strength and depression. 139 pairs of Dizygotic twins were used for bivariate GWAS. VEAGSE2 and PASCAL software were used for gene-based analysis and pathway enrichment analysis, respectively. And the resulting SNPs were subjected to eQTL analysis and pleiotropy analysis. The genetic correlation coefficient between grip strength and depression was -0.41 (-0.96, -0.15). In SNP-based analysis, 7 SNPs exceeded the genome-wide significance level (P<5×10-8) and a total of 336 SNPs reached the level of suggestive significance (P<1×10-5). Gene-based analysis and pathway-based analysis identified genes and pathways related to muscle strength and the nervous system. The results of eQTL analysis were mainly enriched in tissues such as the brain, thyroid, and skeletal muscle. Pleiotropy analysis shows that 9 of the 15 top SNPs were associated with both grip strength and depression. In conclusion, this bivariate GWAS identified potentially common pleiotropic SNPs, genes, and pathways in grip strength and depression.

Bivariate GWAS reveals pleiotropic regions among feed efficiency and beef quality-related traits in Nelore cattle.

Feed-efficient cattle selection is among the most leading solutions to reduce cost for beef cattle production. However, technical difficulties in measuring feed efficiency traits had limited the application in livestock. Here, we performed a Bivariate Genome-Wide Association Study (Bi-GWAS) and presented candidate biological mechanisms underlying the association between feed efficiency and meat quality traits in a half-sibling design with 353 Nelore steers derived from 34 unrelated sires. A total of 13 Quantitative Trait Loci (QTL) were found explaining part of the phenotypic variations. An important transcription factor of adipogenesis in cattle, the TAL1 (rs133408775) gene located on BTA3 was associated with intramuscular fat and average daily gain (IMF-ADG), and a region located on BTA20, close to CD180 and MAST4 genes, both related to fat accumulation. We observed a low positive genetic correlation between IMF-ADG (r = 0.30 ± 0.0686), indicating that it may respond to selection in the same direction. Our findings contributed to clarifying the pleiotropic modulation of the complex traits, indicating new QTLs for bovine genetic improvement.

Exploring the Genetic Association between Obesity and Serum Lipid Levels Using Bivariate Methods.

It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

Association between olfactory pathway gene variants and obesity in Chinese Han population: A case-control study based on genetic score.

Our previous bivariate genome-wide association study in dizygotic twins suggested that the olfactory transduction pathway genes were associated with obesity in Northern Han Chinese adults. In this study, we attempted to verify the associations of the olfactory transduction pathway genes score with obesity in population with the same genetic background, and to estimate the interaction between gene variants and potential environment factors. A case-control study was conducted in Qingdao, China in 2019-2021, which enrolled 301 obesity cases and 307 controls. Based on the candidate gene selection method, 29 single nucleotide polymorphisms (SNPs) in 7 olfactory pathway genes were selected. Genomic deoxyribonucleic acid (DNA) was isolated and purified from the peripheral blood leukocytes by using DNA extraction kits and was genotyped by the MassArray system. The weighted genetic score of each gene was calculated to analyze the effect of whole gene. The effect of gene scores on obesity and the gene-environment interaction were estimated by logistic regression. After adjusting for age, sex, smoking, alcohol drinking, physical activity, we observed positive associations of OR4D1 (OR=1.531, 95% CI=1.083-2.164, P=0.016) and OR52K1 (OR=1.437, 95% CI=1.055-1.957, P=0.022) gene scores with obesity, as well as negative associations of OR2L8 (OR=0.708, 95% CI=0.504-0.995, P=0.046) and CALML3 (OR=0.601, 95% CI=0.410-0.881, P=0.009) gene scores with obesity. Significant multiplicative model interaction between OR4D1 and smoking (Pinteraction=0.041) as well as CALML3 and smoking (Pinteraction=0.026) on obesity were identified. Stratified analysis showed that in smokers, OR4D1 gene score was positively associated with obesity (OR=2.673, 95% CI=1.348-5.299, P=0.005) and CALML3 gene score was negatively correlated with obesity (OR=0.252, 95% CI=0.103-0.618, P=0.003). The relationships were not statistically significant in non-smokers (OR4D1: OR=1.216, 95% CI=0.806-1.836, P=0.351; CALML3: OR=0.764, 95% CI=0.492-1.188, P=0.232). Genetic variations in the olfactory pathway were associated with obesity in Northern Han Chinese adults. Smoking modified the effect of OR4D1 and CALML3 gene variants on obesity.

Potential genetic biomarkers are found to be associated with both cognitive function and blood pressure: A bivariate genome-wide association analysis

A bivariate genome-wide association study was conducted in 137 pairs of twins to explore the shared genetic loci between cognition and blood pressure (BP). Before SNPs imputation, rs72815554 is significantly (P < 5 × 10−8) associated with the cognition-pulse pressure (PP) phenotype, while after imputation, 4 and 9 SNPs are significantly associated with the cognition-SBP phenotype, and cognition-PP phenotype, respectively, including rs72815554. There existed SNPs with highly linkage disequilibrium (LD) of rs10998339, rs72815554, rs11665292, and rs10823231. Besides, rs10998347, rs12153038, and rs10998295 had higher RegulomeDB scores and are located in the transcription factors binding regions. Rs7574283 and rs58113664 are located in the super-enhancer regions which are expressed highly in the adrenal gland, artery, atrial tissue, brain, nerves, etc. There are 1108, 1154, 1071, and 1102 genes associated with cognition-SBP, cognition-DBP, cognition-PP, and cognition-mean arterial pressure (MAP) phenotypes at the suggestive significant association level (P < 0.05), respectively. Furthermore, 641, 630, 900, and 555 pathways are associated with cognition-SBP, cognition-DBP, cognition-PP, and cognition-MAP phenotypes at the suggestive significant association level (P < 0.05), respectively.

14 Genome-wide Association Studies of Disease Resilience Traits from a Natural Polymicrobial Disease Challenge in Pigs

Abstract Infectious diseases cause tremendous financial loss in the pork industry, emphasizing the importance of disease resilience, which is the ability of an animal to maintain performance under disease. The objective of this study was to identify quantitative trait loci (QTL) for disease resilience based on both univariate and bivariate genome-wide association studies (GWAS). Data used were late nursery and finisher growth rates and clinical disease phenotypes, including medical treatment and mortality rates, subjective health scores, feed and water intake traits and carcass traits, collected on 50 batches of 60 or 75 crossbred (LRxY) barrows under a polymicrobial natural disease challenge. Multiple QTL were detected for all traits. The major histocompatibility complex (MHC) region (22–25 Mb on chromosome 7) was found to be associated with multiple traits, including late nursery and finisher growth rates, average daily feed intake and intake rate, average daily water dispensed, water intake duration, and number of visits to the drinker. The MHC region explained ~13% of genetic variance for late nursery growth rate. Further fine mapping identified four QTL in the MHC region for late nursery growth rate that spanned the class I, II, and III regions. Gene set enrichment analyses found genomic regions associated with resilience phenotypes to be enriched for previously identified disease susceptibility and immune capacity QTL, for genes that were differentially expressed following bacterial or virus infection and immune response, and for gene ontology terms related to immune and inflammatory response. In conclusion, MHC and other QTL identified play an important role in host response to infectious diseases and can be incorporated in selection to improve disease resilience. Funded by Genome Canada, Genome Alberta, USDA-NIFA, and PigGen Canada.

BTOB: Extending the Biased GWAS to Bivariate GWAS.

In recent years, a number of literatures published large-scale genome-wide association studies (GWASs) for human diseases or traits while adjusting for other heritable covariate. However, it is known that these GWASs are biased, which may lead to biased genetic estimates or even false positives. In this study, we provide a method called “BTOB” which extends the biased GWAS to bivariate GWAS by integrating the summary association statistics from the biased GWAS and the GWAS for the adjusted heritable covariate. We employ the proposed BTOB method to analyze the summary association statistics from the large scale meta-GWASs for waist-to-hip ratio (WHR) and body mass index (BMI), and show that the proposed approach can help identify more susceptible genes compared with the corresponding univariate GWASs. Theoretical results and simulations also confirm the validity and efficiency of the proposed BTOB method.

Bivariate genome-wide association study (GWAS) of body mass index and blood pressure phenotypes in northern Chinese twins.

Recently, new loci related to body mass index (BMI) or blood pressure (BP) have been identified respectively in genome-wide association studies (GWAS). However, limited studies focused on jointly associated genetic variance between systolic pressure (SBP), diastolic pressure (DBP) and BMI. Therefore, a bivariate twin study was performed to explore the genetic variants associated with BMI-SBP, BMI-DBP and SBP-DBP. A total of 380 twin pairs (137 dizygotic pairs and 243 monozygotic pairs) recruited from Qingdao Twin Registry system were used to access the genetic correlations (0.2108 for BMI-SBP, 0.2345 for BMI-DBP, and 0.6942 for SBP-DBP, respectively) by bivariate Cholesky decomposition model. Bivariate GWAS in 137 dizygotic pairs nominated 27 single identified 27 quantitative trait nucleotides (QTNs) for BMI and SBP, 27 QTNs for BMI and DBP, and 25 QTNs for SBP and DBP with the suggestive P-value threshold of 1×10−5. After imputation, we found eight SNPs, one for both BMI-SBP and SBP-DBP, and eight for SBP-DBP, exceed significant statistic level. Expression quantitative trait loci analysis identified rs4794029 as new significant eQTL in tissues related to BMI and SBP. Also, we found 6 new significant eQTLs (rs4400367, rs10113750, rs11776003, rs3739327, rs55978930, and rs4794029) in tissues were related to SBP and DBP. Gene-based analysis identified nominally associated genes (P < 0.05) with BMI-SBP, BMI-DBP, and SBP-DBP, respectively, such as PHOSPHO1, GNGT2, KEAP1, and S1PR5. In the pathway analysis, we found some pathways associated with BMI-SBP, BMI-DBP and SBP-DBP, such as prion diseases, IL5 pathway, cyclin E associated events during G1/S transition, TGF beta signaling pathway, G βγ signaling through PI3Kγ, prolactin receptor signaling etc. These findings may enrich the results of genetic variants related to BMI and BP traits, and provide some evidences to future study the pathogenesis of hypertension and obesity in the northern Chinese population.

Multi-trait association studies discover pleiotropic loci between Alzheimer\u2019s disease and cardiometabolic traits

BackgroundIdentification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits.MethodsWe performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes.ResultsWe identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE, the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic.ConclusionOur results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

Genome-wide association studies for mottled eggs in chickens using a high-density single-nucleotide polymorphism array

Mottled eggs in layer chickens are gaining increasing attention because of the economic impact on the egg industry caused by the reduced sale value of commodity eggs. However, the genetic architecture underlying mottled eggs is not well understood. The genetic architecture underlying the mottled egg trait was investigated using genome-wide association studies (GWAS) by high-density arrays, using a total of 407 pink eggs and 799 blue eggs from an F2 resource population generated by crossing Dongxiang Blue-shelled and White Leghorn chickens. The mottled egg score in blue eggs was found to be higher than that in pink eggs. The single-nucleotide polymorphism heritability of mottled egg at laying day and storage for 7 days was 0.18 and 0.20, respectively. Bivariate GWAS provided 29 significant loci, mainly located on GGA2, GGA3, GGA8, GGA10, GGA15, GGA17, and GGA23, affecting mottled egg on laying day. Candidate genes RIMS2, SLC25A32, RIMBP2, VPS13B, and RGS3 were obtained for mottled eggshell by bivariate GWAS and gene annotation. Our findings provide new insights into the genetic architecture of mottled egg in hens, and demonstrate that a genomic selection method would be profitable for breeding out the mottled egg trait.

27 Genomic relationship between antibody response to porcine reproductive and respiratory syndrome virus vaccination and reproductive performance in commercial sows

Abstract Antibody response, measured as sample-to-positive ratio (S/P), to porcine reproductive and respiratory syndrome (PRRS) after PRRS outbreaks has been proposed as an indicator trait to improve reproductive performance in PRRS-infected sows. However, waiting for a PRRS outbreak to occur and having different relationships in healthy pigs may limit the use of this trait. Thus, we proposed to investigate if this relationship also occurs between S/P to PRRS vaccination and reproductive performance in sows without exposure to PRRS. Nine hundred six F1 replacement gilts (139□17 days old) from two commercial farms were vaccinated with a commercial modified live PRRS virus vaccine. Blood samples were collected at 52 days after vaccination to measure S/P to PRRS and SNP genotyping. Reproductive performance included: number born alive (NBA), number of piglets weaned, number born mummified (MUM), number stillborn (NSB), and pre-weaning mortality (PWM) at parities (P) 1 to 3. Average performance was calculated for each trait per sow per year (PSY). Farrowing rate and age at first service were also analyzed. BayesC0 was used to estimate genetic correlations between S/P and reproductive performance. Bivariate genome-wide association studies of antibody response and reproductive traits were performed using BayesB. High genetic correlations between S/P and farrowing performance were identified for NBA_P1 (0.61±0.16), PWM_P2 (-0.64±0.15), PWM_P2 (-0.63±0.20), NSB_P3 (-0.84±0.05), MUM_P3 (-0.83±0.11), and NSB_PSY (-0.90±0.05). A QTL was identified on chromosome 7 (MHC region) for these reproductive traits and for S/P, explaining from 1.2% (PWM_P2) to 22.4% (S/P) of the genetic variance. SNP H3GA0020505 explained most of the variance in this region for these traits. Heterozygote animals for this SNP had overall better performance: greater S/P (P = 0.001), greater (P = 0.06) NBA_P1, and lesser (P = 0.06) MUM_P3 than other genotypes. These results suggest that antibody response to PRRS vaccination may be used as a genetic indicator to improve reproductive performance in commercial pigs.

Three pleiotropic loci associated with bone mineral density and lean body mass.

Both bone mineral density (BMD) and lean body mass (LBM) are important physiological measures with strong genetic determination. Besides, BMD and LBM might have common genetic factors. Aiming to identify pleiotropic genomic loci underlying BMD and LBM, we performed bivariate genome-wide association study meta-analyses of femoral neck bone mineral density and LBM at arms and legs, and replicated in the large-scale UK Biobank cohort sample. Combining the results from discovery meta-analysis and replication sample, we identified three genomic loci at the genome-wide significance level (p < 5.0 × 10-8): 2p23.2 (lead SNP rs4477866, discovery p = 3.47 × 10-8, replication p = 1.03 × 10-4), 16q12.2 (rs1421085, discovery p = 2.04 × 10-9, replication p = 6.47 × 10-14) and 18q21.32 (rs11152213, discovery p = 3.47 × 10-8, replication p = 6.69 × 10-6). Our findings not only provide useful insights into lean mass and bone mass development, but also enhance our understanding of the potential genetic correlation between BMD and LBM.

Identification of pleiotropic loci underlying hip bone mineral density and trunk lean mass.

Bone mineral density (BMD) and lean body mass (LBM) not only have a considerable heritability each, but also are genetically correlated. However, common genetic determinants shared by both traits are largely unknown. In the present study, we performed a bivariate genome-wide association study (GWAS) meta-analysis of hip BMD and trunk lean mass (TLM) in 11,335 subjects from 6 samples, and performed replication in estimated heel BMD and TLM in 215,234 UK Biobank (UKB) participants. We identified 2 loci that nearly attained the genome-wide significance (GWS, p < 5.0 × 10-8) level in the discovery GWAS meta-analysis and that were successfully replicated in the UKB sample: 11p15.2 (lead SNP rs12800228, discovery p = 2.88 × 10-7, replication p = 1.95 × 10-4) and 18q21.32 (rs489693, discovery p = 1.67 × 10-7, replication p = 1.17 × 10-3). The above 2 pleiotropic loci may play a pleiotropic role for hip BMD and TLM development. So our findings provide useful insights that further enhance our understanding of genetic interplay between BMD and LBM.

Genetic Analysis of Antibody Response to Porcine Reproductive and Respiratory Syndrome Vaccination as an Indicator Trait for Reproductive Performance in Commercial Sows.

We proposed to investigate the genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) vaccination and its relationship to reproductive performance in non-PRRSV-infected commercial sows. Nine hundred and six F1 replacement gilts (139 ± 17 days old) from two commercial farms were vaccinated with a commercial modified live PRRSV vaccine. Blood samples were collected about 52 days after vaccination to measure antibody response to PRRSV as sample-to-positive (S/P) ratio and for single-nucleotide polymorphism (SNP) genotyping. Reproductive performance was recorded for up to 807 sows for number born alive (NBA), number of piglets weaned, number born mummified (MUM), number of stillborn (NSB), and number of pre-weaning mortality (PWM) at parities (P) 1–3 and per sow per year (PSY). Fertility traits such as farrowing rate and age at first service were also analyzed. BayesC0 was used to estimate heritability and genetic correlations of S/P ratio with reproductive performance. Genome-wide association study (GWAS) and genomic prediction were performed using BayesB. The heritability estimate of S/P ratio was 0.34 ± 0.05. High genetic correlations (rg) of S/P ratio with farrowing performance were identified for NBA P1 (0.61), PWM P2 (-0.70), NSB P3 (-0.83), MUM P3 (-0.84), and NSB PSY (-0.90), indicating that genetic selection for increased S/P ratio would result in improved performance of these traits. A quantitative trait locus was identified on chromosome 7 (∼25 Mb), at the major histocompatibility complex (MHC) region, explaining ∼30% of the genetic variance for S/P ratio, mainly by SNPs ASGA0032113, H3GA0020505, and M1GA0009777. This same region was identified in the bivariate GWAS of S/P ratio and reproductive traits, with SNP H3GA0020505 explaining up to 10% (for NBA P1) of the genetic variance of reproductive performance. The heterozygote genotype at H3GA0020505 was associated with greater S/P ratio and NBA P1 (P = 0.06), and lower MUM P3 and NSB P3 (P = 0.07). Genomic prediction accuracy for S/P ratio was high when using all SNPs (0.67) and when using only those in the MHC region (0.59) and moderate to low when using all SNPs excluding those in the MHC region (0.39). These results suggest that there is great potential to use antibody response to PRRSV vaccination as an indicator trait to improve reproductive performance in commercial pigs.

Bivariate genome-wide association study of the growth plasticity of Staphylococcus aureus in coculture with Escherichia coli.

Phenotypic plasticity is the capacity to change the phenotype in response to different environments without alteration of the genotype. Despite sufficient evidence that microorganisms have a major role in the fitness and sickness of eukaryotes, there has been little research regarding microbial phenotypic plasticity. In this study, 45 strains of Staphylococcus aureus were grown for 12days in both monoculture and in coculture with the same strain of Escherichia coli to create a competitive environment. Cell abundance was determined by quantitative PCR every 24h, and growth curves of each S. aureus strain under the two sets of conditions were generated. Combined with whole-genome resequencing data, bivariate genome-wide association study (GWAS) was performed to analyze the growth plasticity of S. aureus in coculture. Finally, 20 significant single-nucleotide polymorphisms (eight annotated, seven unannotated, and five non-coding regions) were obtained, which may affect the competitive growth of S. aureus. This study advances genome-wide bacterial growth plasticity research and demonstrates the potential of bivariate GWAS for bacterial phenotypic plasticity research. KEY POINTS: • Growth plasticity of S. aureus was analyzed by bivariate GWAS. • Twenty significant SNPs may affect the growth plasticity of S. aureus.

Phenotypic Plasticity of Staphylococcus aureus in Liquid Medium Containing Vancomycin.

Phenotypic plasticity enables individuals to develop different phenotypes in a changing environment and promotes adaptive evolution. Genome-wide association study (GWAS) facilitates the study of the genetic basis of bacterial phenotypes, and provides a new opportunity for bacterial phenotypic plasticity research. To investigate the relationship between growth plasticity and genotype in bacteria, 41 Staphylococcus aureus strains, including 29 vancomycin-intermediate S. aureus (VISA) strains, were inoculated in the absence or presence of vancomycin for 48 h. Growth curves and maximum growth rates revealed that strains with the same minimum inhibitory concentration (MIC) showed different levels of plasticity in response to vancomycin. A bivariate GWAS was performed to map single-nucleotide polymorphisms (SNPs) associated with growth plasticity. In total, 227 SNPs were identified from 14 time points, while 15 high-frequency SNPs were mapped to different annotated genes. The P-values and growth variations between the two cultures suggest that non-coding region (SNP 738836), ebh (SNP 1394043), drug transporter (SNP 264897), and pepV (SNP 1775112) play important roles in the growth plasticity of S. aureus. Our study provides an alternative strategy for dissecting the adaptive growth of S. aureus in vancomycin and highlights the feasibility of bivariate GWAS in bacterial phenotypic plasticity research.

Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease.

Plasma lipid levels are heritable and genetically associated with risk of coronary artery disease (CAD). However, genome-wide association studies (GWAS) routinely analyze these traits independent of one another. Joint GWAS for two related phenotypes can lead to a higher powered analysis to detect variants contributing to both traits. We performed a bivariate GWAS to discover novel loci associated with both heart disease, using a CAD meta-analysis (122 733 cases and 424 528 controls), and lipid traits, using results from the Global Lipid Genetics Consortium (188 577 subjects). We identified six previously unreported loci at genome-wide significance ( P<5×10-8), three which were associated with triglycerides and CAD, two which were associated with LDL (low-density lipoprotein) cholesterol and CAD, and one associated with total cholesterol and CAD. At several of our loci, the GWAS signals jointly localize with genetic variants associated with expression level changes for more than one neighboring genes, indicating that these loci may be affecting disease risk through regulatory activity. We discovered six novel variants individually associated with both lipids and CAD.

Bivariate Genome-Wide Association Study of Depressive Symptoms With Type 2 Diabetes and Quantitative Glycemic Traits.

Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 × 10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes). We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.

Genome-wide association study for feed efficiency traits using SNP and haplotype models.

Feed costs comprise the majority of variable expenses in beef cattle systems making feed efficiency an important economic consideration within the beef industry. Due to the expense of recording individual feed-intake phenotypes, a genomic-enabled approach could be advantageous toward improving this economically relevant trait complex. A genome-wide association study (GWAS) was performed using 748 crossbred steers and heifers representing seven sire breeds with phenotypes for ADG and ADFI. Animals were genotyped with the BovineSNP50v2 BeadChip containing approximately 54,000 SNP. Both traits were analyzed using univariate SNP-based (BayesC) and haplotype-based (BayesIM) models and jointly using BayesIM to perform a bivariate GWAS. For BayesIM, a hidden Markov model (HMM) of haplotype segments of variable length was built where haplotypes were mapped to clusters based on local similarity. The estimated HMM was then used to assign haplotype cluster genotypes, instead of SNP genotypes, as latent covariates in a Bayesian mixture model. The number of haplotype clusters at each location was assumed to be either 8 (BayesIM8) or 16 (BayesIM16). A total of three univariate analyses for each trait and two bivariate analyses were performed. Posterior SD (PSD) for ADG were 0.28 (0.08), 0.37 (0.11), 0.37 (0.11), 0.35 (0.11), and 0.35 (0.12) for BayesC, BayesIM8, BayesIM16, BayesIM8 bivariate, and BayesIM16 bivariate, respectively. ADFI PSD were 0.30 (0.07), 0.44 (0.13), 0.42 (0.12), 0.38 (0.10), and 0.38 (0.10) for the same models. The top 1% of 1-Mb windows that explained the largest fraction of genetic variation in common between univariate SNP and haplotype models ranged from 24% to 40% and from 20% to 32% for ADG and ADFI, respectively. Spearmen rank correlations between molecular breeding values from SNP and haplotype-based models in the training data were similar for both traits (>0.96) suggesting that either model would lead to similar rankings of animals, although resolution of potential QTL appeared to be greater for BayesIM.

Advances on genome-wide association study in diagnosis and treatment of osteoporosis

Osteoporosis is a complex disease caused by genetic and environmental factors, which the genetic architecture is not completely understood. Genome-wide association study (GWAS) have reformed the identification of genetic determinants of complex diseases including osteoporosis. In the past decade, more than 30 GWASes which were related to bone mass density identified nearly 100 independent loci. The bivariate GWAS approach is an effective approach to detect pleiotropic genes for two osteoporosis traits. However, genetic analyses must be combined with functional studies to understand the underlying mechanisms. The insight of bone metabolism by GWAS is of huge potential for the identification of novel drug targets for osteoporosis. (Chin J Lab Med, 2017, 40: 848-851) Key words: Osteoporosis; Genome-wide association study; Bone mineral density; Diagnosis