Non-invasive biomarkers for early diagnosis of pancreatic cancer risk: metabolite genomewide association study based on the KCPS-II cohort.

BACKGROUND: Pancreatic cancer is a lethal disease with a high mortality rate. The difficulty of early diagnosis is one of its primary causes. Therefore, we aimed to discover non-invasive biomarkers that facilitate the early diagnosis of pancreatic cancer risk. METHODS: The study subjects were randomly selected from the Korean Cancer Prevention Study-II and matched by age, sex, and blood collection point [pancreatic cancer incidence (n = 128) vs. control (n = 256)]. The baseline serum samples were analyzed by non-targeted metabolomics, and XGBoost was used to select significant metabolites related to pancreatic cancer incidence. Genomewide association study for the selected metabolites discovered valuable single nucleotide polymorphisms (SNPs). Moderation and mediation analysis were conducted to explore the variables related to pancreatic cancer risk. RESULTS: Eleven discriminant metabolites were selected by applying a cut-off of 4.0 in XGBoost. Five SNP presented significance in metabolite-GWAS (p ≤ 5 × 10-6) and logistic regression analysis. Among them, the pair metabolite of rs2370981, rs55870181, and rs72805402 displayed a different network pattern with clinical/biochemical indicators on comparison with allelic carrier and non-carrier. In addition, we demonstrated the indirect effect of rs59519100 on pancreatic cancer risk mediated by γ-glutamyl tyrosine, which affects the smoking status. The predictive ability for pancreatic cancer on the model using five SNPs and four pair metabolites with the conventional risk factors was the highest (AUC: 0.738 [0.661-0.815]). CONCLUSIONS: Signatures involving metabolites and SNPs discovered in the present research may be closely associated with the pathogenesis of pancreatic cancer and for use as predictive biomarkers allowing early pancreatic cancer diagnosis and therapy.

Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure.

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.

Genetic Susceptibility to Pneumonia: A GWAS Meta-Analysis Between the UK Biobank and FinnGen.

Pneumonia is a respiratory condition with complex etiology. Host genetic variation is thought to contribute to individual differences in susceptibility and symptom manifestation. Here, we analyze pneumonia data from the UK Biobank (14,780 cases and 439,096 controls) and FinnGen (9980 cases and 86,519 controls) and perform a genomewide association study meta-analysis. We use gene-based tests, colocalization, genetic correlation, latent causal variable (LCV) and polygenic prediction in an independent Australian sample (N = 5595) to draw insights into the etiology of pneumonia risk. We identify two independent loci on chromosome 15 (lead single-nucleotide polymorphisms rs2009746 and rs76474922) to be associated with pneumonia (p < 5e-8). Gene-based tests revealed 18 genes in chromosomes 15, 16 and 9, including IL127, PBX3, ApoB receptor (APOBR) and smoking related genes CHRNA3/5, statistically associated with pneumonia. We observed genetic correlations between pneumonia and cardiorespiratory, psychiatric and inflammatory related traits. LCV analysis suggests a strong genetic causal relationship with cardiovascular health phenotypes. Polygenic risk scores for pneumonia significantly predicted self-reported pneumonia in an independent sample, albeit with a small effect size (OR = 1.11 95% CI [1.04, 1.19], p < .05). Sensitivity analyses suggested the associations in chromosome 15 are mediated by smoking history, but the associations in chromosomes 16 and 9, and polygenic prediction were robust to adjustment for smoking. Altogether, our results highlight common genetic variants, genes and potential pathways that contribute to individual differences in susceptibility to pneumonia, and advance our understanding of the genetic factors underlying heterogeneity in respiratory medical outcomes.

Genome-Wide Associations and Transcriptional Profiling Reveal ROS Regulation as One Underlying Mechanism of Sheath Blight Resistance in Rice.

Rice sheath blight, caused by the necrotrophic fungus Rhizoctonia solani Kühn, continues to be an important and challenging rice disease worldwide. Here, we used genome-wide association studies over a high-density rice array to facilitate the identification of potential novel genes and quantitative trait loci related to sheath blight resistance. We identified multiple regions that significantly associated with independent disease components in chromosomes 1, 4, and 11 under controlled condition. In particular, we investigated qLN1128, a quantitative trait locus enriched with defense-related genes that reduce disease lesions in a near-isogenic line. RNA profiling of the line carrying qLN1128 showed a number of differentially expressed genes related to the reactive oxygen species (ROS)-redox pathway. Histochemical staining revealed less ROS accumulation on the resistant line, suggesting efficient ROS deregulation that delays pathogen colonization. The detection of genomic regions controlling multiple mechanisms of resistance to sheath blight will provide tools to design effective breeding interventions in rice.

Gene Discovery Using Twins.

One of Nick's key early achievements at QIMR was to establish a twin study on melanoma risk factors. The Brisbane Twin Nevus Study (BTNS) had an initial focus on nevus (mole) count in adolescents but, reflecting Nick's broad interests, expanded in scope enormously over the decades. In the skin cancer arena, BTNS was essential to genetic discoveries in melanoma, eye color and pigmentation. Later studies amassed data on thousands of phenotypes, ranging from molecular phenotypes such as gene expression to studies where gene mapping findings in adolescents turned out to have translational potential in late-onset diseases. Nick's twin data have formed the basis for an enormous range of discoveries, with Nick and his colleagues continuing to capitalize on these data.

It's in the Bloody Genes!

Blood cell concentrations for most cell types are highly heritable. Data from Nick Martin's twin registry provided much of the data for the early heritability and linkage studies of blood cell related traits and have contributed significantly to more recent genomewide association studies that have successfully identified individual genetic loci.

Contributions of Nicholas Martin to Gambling Disorder Research.

Professor Nicholas G. Martin, from QIMR Berghofer Medical Research Institute in Brisbane, Australia, is a world leader in the effort to understand the genetic architecture underlying disordered gambling. This article pays tribute to Nick and his almost two decades of gambling research, highlighting his many strengths, ranging from the use of ingenious recruitment approaches, twin study methods, genomewide association studies, to facilitating international collaborations.

Genomewide association study of Parkinson's disease clinical biomarkers in 12 longitudinal patients' cohorts.

BACKGROUND: Several reports have identified different patterns of Parkinson's disease progression in individuals carrying missense variants in GBA or LRRK2 genes. The overall contribution of genetic factors to the severity and progression of Parkinson's disease, however, has not been well studied. OBJECTIVES: To test the association between genetic variants and the clinical features of Parkinson's disease on a genomewide scale. METHODS: We accumulated individual data from 12 longitudinal cohorts in a total of 4093 patients with 22,307 observations for a median of 3.81 years. Genomewide associations were evaluated for 25 cross-sectional and longitudinal phenotypes. Specific variants of interest, including 90 recently identified disease-risk variants, were also investigated post hoc for candidate associations with these phenotypes. RESULTS: Two variants were genomewide significant. Rs382940(T>A), within the intron of SLC44A1, was associated with reaching Hoehn and Yahr stage 3 or higher faster (hazard ratio 2.04 [1.58-2.62]; P value = 3.46E-8). Rs61863020(G>A), an intergenic variant and expression quantitative trait loci for α-2A adrenergic receptor, was associated with a lower prevalence of insomnia at baseline (odds ratio 0.63 [0.52-0.75]; P value = 4.74E-8). In the targeted analysis, we found 9 associations between known Parkinson's risk variants and more severe motor/cognitive symptoms. Also, we replicated previous reports of GBA coding variants (rs2230288: p.E365K; rs75548401: p.T408M) being associated with greater motor and cognitive decline over time, and an APOE E4 tagging variant (rs429358) being associated with greater cognitive deficits in patients. CONCLUSIONS: We identified novel genetic factors associated with heterogeneity of Parkinson's disease. The results can be used for validation or hypothesis tests regarding Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Identification of genetic risk factors of aggressive periodontitis using genomewide association studies in association with those of chronic periodontitis.

To identify the genetic risk factors for aggressive periodontitis (AgP), it is important to understand the progression and pathogenesis of AgP. The purpose of this review was to summarize the genetic risk factors for AgP identified through a case-control genomewide association study (GWAS) and replication study. The initial studies to identify novel AgP risk factors were potentially biased because they relied on previous studies. To overcome this kind of issue, an unbiased GWAS strategy was introduced to identify genetic risk factors for various diseases. Currently, three genes glycosyltransferase 6 domain containing 1 (GLT6D1), defensin α1 and α3 (DEFA1A3), and sialic acid-binding Ig-like lectin 5 (SIGLEC5) that reach the threshold for genomewide significance have been identified as genetic risk factors for AgP through a case-control GWAS.

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum.

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole-genome resequencing and genotyping by sequencing (GBS) were used to construct high-density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum-clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co-located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS-GWAS represent a powerful combined approach for the identification of loci controlling complex traits.

Natural variation in stomata size contributes to the local adaptation of water-use efficiency in Arabidopsis thaliana.

Stomata control gas exchanges between the plant and the atmosphere. How natural variation in stomata size and density contributes to resolve trade-offs between carbon uptake and water loss in response to local climatic variation is not yet understood. We developed an automated confocal microscopy approach to characterize natural genetic variation in stomatal patterning in 330 fully sequenced Arabidopsis thaliana accessions collected throughout the European range of the species. We compared this to variation in water-use efficiency, measured as carbon isotope discrimination (δ13 C). We detect substantial genetic variation for stomata size and density segregating within Arabidopsis thaliana. A positive correlation between stomata size and δ13 C further suggests that this variation has consequences on water-use efficiency. Genome wide association analyses indicate a complex genetic architecture underlying not only variation in stomatal patterning but also to its covariation with carbon uptake parameters. Yet, we report two novel QTL affecting δ13 C independently of stomatal patterning. This suggests that, in A. thaliana, both morphological and physiological variants contribute to genetic variance in water-use efficiency. Patterns of regional differentiation and covariation with climatic parameters indicate that natural selection has contributed to shape some of this variation, especially in Southern Sweden, where water availability is more limited in spring relative to summer. These conditions are expected to favour the evolution of drought avoidance mechanisms over drought escape strategies.

Genomewide Association Study of Alcohol Dependence and Related Traits in a Thai Population.

BACKGROUND: Alcohol use (both quantity and dependence) is moderately heritable, and genomewide association studies (GWAS) have identified risk genes in European, African, and Asian populations. The most reproducibly identified risk genes affect alcohol metabolism. Well-known functional variants at the gene encoding alcohol dehydrogenase B and other alcohol dehydrogenases affect risk in European and African ancestry populations. Similarly, variants mapped to these same genes and a well-known null variant that maps to the gene that encodes aldehyde dehydrogenase 2 (ALDH2) also affect risk in various Asian populations. In this study, we completed the first GWAS for 3 traits related to alcohol use in a Thai population recruited initially for studies of methamphetamine dependence. METHODS: All subjects were evaluated with the Thai version of the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA). A total of 1,045 subjects were available for analysis. Three traits were analyzed: flushing, maximum number of alcoholic beverages consumed in any lifetime 24-hour period ("MAXDRINKS"), and DSM-IV alcohol dependence criterion count. We also conducted a pleiotropy analysis with major depression, the only other psychiatric trait where summary statistics from a large-scale Asian-population GWAS are available. RESULTS: All 3 traits showed genomewide significant association with variants near ALDH2, with significance ranging from 2.01 × 10-14 (for flushing; lead single nucleotide polymorphism (SNP) PTPN11* rs143894582) to pmeta  = 5.80 × 10-10 (for alcohol dependence criterion count; lead SNP rs149212747). These lead SNPs flank rs671 and span a region of over a megabase, illustrating the need for prior biological information in identifying the actual effect SNP, rs671. We also identified significant pleiotropy between major depression and flushing. CONCLUSIONS: These results are consistent with prior findings in Asian populations and add new information regarding alcohol use-depression pleiotropy.

Genomewide association study reveals novel genetic loci associated with change in renal function in heart transplant recipients.

BACKGROUND: Renal dysfunction occurs commonly after heart transplantation (HTx) with wide inter-individual variability but whether a genetic predisposition exists in these patients is unknown. Genomewide association studies (GWAS) have not been performed to assess the association of genetic variation with change in renal function after HTx. METHODS: Clinical and demographic data of patients who underwent HTx and provided blood samples and consent for genetic analysis were included. Genotyping was performed using Illumina Infinium Human CoreExome v1.0 analysis kit. A GWAS utilizing linear regression models was performed with estimated glomerular filtration rate (eGFR) at 1 year as the phenotype after adjusting for baseline eGFR prior to HTx and conversion from calcineurin inhibitor to sirolimus as primary immunosuppression therapy. RESULTS: A total of 251 HTx recipients were genotyped for 314,903 single nucleotide polymorphisms (SNPs). The mean (SD) age was 50 (12.5) years; most patients were of European origin (n = 243, 96.8%) and males (n = 179, 71.3%). After adjustment for potential confounders, two variants, rs17033285 (P = 4.3 × 10-7 ) and rs4917601 (P = 6.46 × 10-7 ), in a long non-coding RNA (lncRNA) gene LINC01121 and a pseudogene BTBD7P2, were identified to have a significant association with change in GFR at 1 year after HTx. CONCLUSIONS: Our first of its kind GWAS demonstrates that genetic variation affects renal function after HTx independent of other risk factors. Agnostic genetic approaches such as these may lead to identification of novel biological pathways such as the role of lncRNAs in the development of renal dysfunction post-HTx.

Evaluating the effect of nicotinic cholinergic receptor genes on the risk of nonsyndromic cleft lip with or without cleft palate.

OBJECTIVE: Multiple studies have suggested nonsyndromic cleft lip with or without cleft palate (NSCL/P), and lung cancer may have common genetic etiology. Previous studies have showed genetic variants in nicotinic cholinergic receptor genes (CHRNs) may influence risk of lung cancer. We aimed to explore the effect of CHRNs on risk of NSCL/P considering gene-gene (GxG) interaction for these genes. SUBJECTS AND METHODS: We selected 120 markers in 14 CHRNs to test for GxG interaction using 806 Chinese case-parent trios recruited from an international consortium established for a GWAS of oral clefts. RESULTS: Totally, two pairs of SNPs yielded significant GxG interactions after Bonferroni correction (rs935865 and rs2337980 with p = 4.04 × 10-5 , rs2741335 and rs3743077 with p = 4.80 × 10-4 ), and these pairwise interactions were confirmed in permutation tests. In addition, the relative risk (RR) of the putative interaction between rs935865 and rs2337980 was 1.10 (95% CI: 0.92~1.31). CONCLUSIONS: While the single SNP association and the gene-environment interaction analysis of 14 CHRN genes yielded no signal, this study did demonstrate the importance of considering potential GxG interaction for exploring etiology of NSCL/P. This study suggests an important role for particular combinations of SNPs in CHRN genes in influencing risk to NSCL/P, which needs further study.

The genetic architecture of defence as resistance to and tolerance of bacterial infection in Drosophila melanogaster.

Defence against pathogenic infection can take two forms: resistance and tolerance. Resistance is the ability of the host to limit a pathogen burden, whereas tolerance is the ability to limit the negative consequences of infection at a given level of infection intensity. Evolutionarily, a tolerance strategy that is independent of resistance could allow the host to avoid mounting a costly immune response and, theoretically, to avoid a co-evolutionary arms race between pathogen virulence and host resistance. Biomedically, understanding the mechanisms of tolerance and how they relate to resistance could potentially yield treatment strategies that focus on health improvement instead of pathogen elimination. To understand the impact of tolerance on host defence and identify genetic variants that determine host tolerance, we defined genetic variation in tolerance as the residual deviation from a binomial regression of fitness under infection against infection intensity. We then performed a genomewide association study to map the genetic basis of variation in resistance to and tolerance of infection by the bacterium Providencia rettgeri. We found a positive genetic correlation between resistance and tolerance, and we demonstrated that the level of resistance is highly predictive of tolerance. We identified 30 loci that predict tolerance, many of which are in genes involved in the regulation of immunity and metabolism. We used RNAi to confirm that a subset of mapped genes have a role in defence, including putative wound repair genes grainy head and debris buster. Our results indicate that tolerance is not an independent strategy from resistance, but that defence arises from a collection of physiological processes intertwined with canonical immunity and resistance.

[Multilocus genetic analysis implicates neurodevelopment and immune system in the etiology of schizophrenia]. / A szkizofrénia multilókusz genetikai vizsgálata az idegfejlodés és az immunrendszer zavarának oki szerepére utal(hat).

BACKGROUND AND PURPOSE: Schizophrenia is a severe psychiatric disorder of poorly understood etiology, characterized by high heritability, multifactorial inheritance and high heterogeneity. Multilocus associaton methods may reduce the genetic heterogeneity and improve the probability of replication between analyses. The aims of our study were twofold: 1. To analyse genetic risk factors of schizophrenia by using multilocus genetic tests. 2. To assess the replication probability attributable to the various multilocus tests. METHODS: Subjects - Discovery set: case-parent trios of unaffected parents and affected probands with a DSM-IV schizophrenia diagnosis (n=16); replication set: schizophrenia cases and unaffected controls (n=5337). Associations of single nucleotide and indel markers were transferred to gene- and geneset-based associations, furthermore to geneset-enrichment tests and functional annotation cluster analyses in a two-staged designs. Associations with p<0.1 from the discovery set were tested in the replication sample. Familywise p-value correction for multiple comparisons were performed during the replication step. RESULTS: After correction for multiplicity, no significant association or enrichment were detected for gene-based nor canonical pathway analyses, but significant association of the 14q31 cytoband and enrichments of the 5q31 and Xq13 cytobands were found (p_corr: 0.002, 0.006 and 0.048, respectively). Functional annotation clustering yielded statistically significant enrichment scores for clusters of splicing/alternative splicing, neurodevelopment and embryonic development. Improvements in replication probability were found with increased test complexity (P_rep: 0, 0.015, 0.21). CONCLUSION: Our results corroborate the involvement of neurodevelopment, synaptic plasticity and immune mechanisms in the etiology of schizophrenia. Also, our findings indicated improvement of replication probability by using multilocus genetic analyses.

The migraine-stroke connection: A genetic perspective.

BACKGROUND: A complex relationship between migraine and vascular disease has long been recognized. The pathophysiological basis underlying this correlation is incompletely understood. AIM: The aim of this review is to focus on the migraine-vascular disorders connection from a genetic perspective, illustrating potentially shared (molecular) mechanisms. RESULTS: We first summarize the clinical presentation and genetic basis of CADASIL and other monogenic vascular syndromes with migraine as a prominent disease manifestation. Based on data from transgenic mouse models for familial hemiplegic migraine, we then discuss cortical spreading depression as a potential mechanistic link between migraine and ischemic stroke. Finally, we review data from genome-wide association studies, with a focus on overlapping findings with cervical artery dissection, ischemic stroke in general and cardiovascular disease. CONCLUSION: A wealth of data supports a genetic link between migraine and vascular disease. Based on growing high-throughput data-sets, new genotyping techniques and in-depth phenotyping, further insights are expected for the future.

Genetic effects of multiple asthma loci identified by genomewide association studies on asthma and spirometric indices.

BACKGROUND: Genomewide association study (GWAS) published by GABRIEL consortium identified 10 asthma-associated loci. However, their relationship with lung functions is unclear. This study investigated the association between asthma traits and single-nucleotide polymorphisms (SNPs) of these GWAS loci. METHODS: Rs3894194 and rs9273349 were not genotyped due to unavailable TaqMan assays. Genetic associations of remaining eight SNPs were investigated in 903 school-age asthmatics and 1205 non-allergic controls. Four significant SNPs were then replicated in 479 adult asthmatics and 746 adult controls, and 1341 Chinese preschool children. Meta-analyses were performed by combining data from school-age children and adults. Generalized multifactor dimensionality reduction (GMDR) was used to analyze their interactions for asthma traits. RESULTS: Childhood asthma was associated with GSDMB_rs2305480 (odds ratio [OR] 0.69, 95% confidence interval [CI] 0.57-0.83). IL13_rs1295686 was associated with all asthma (OR 1.64, 95% CI 1.16-2.32) and early-onset asthma (OR 1.92, 95% CI 1.20-3.06) in adults, whereas GSDMB_rs2305480 was only associated with early-onset asthma (OR 0.69, 95% CI 0.49-0.96). According to meta-analyses, the minor allele of rs2305480 was inversely associated with FEV1 , FVC, and FEV1 /FVC (p < 0.01). GMDR analyses revealed 2-locus models of SLC22A5 with SMAD3 to modulate FEVt /FVC in both preschool children and adults, with IL13 to determine FVC in both school-age children and adults, and with IL2RB to modulate FEV1 /FVC in school-age children. CONCLUSIONS: IL13 and GSDMB are replicated as asthma genes. Rs2305480 of GSDMB is also associated with low FEV1 , FVC, and FEV1 /FVC among asthmatics. Moreover, SLC22A5, IL13, SMAD3, and GSDMB interact to modulate spirometric indices.

Genome-wide association studies and resting heart rate.

Genome-wide association studies (GWASs) have revolutionized the search for genetic variants regulating resting heart rate. In the last 10years, GWASs have led to the identification of at least 21 novel heart rate loci. These discoveries have provided valuable insights into the mechanisms and pathways that regulate heart rate and link heart rate to cardiovascular morbidity and mortality. GWASs capture majority of genetic variation in a population sample by utilizing high-throughput genotyping chips measuring genotypes for up to several millions of SNPs across the genome in thousands of individuals. This allows the identification of the strongest heart rate associated signals at genome-wide level. While GWASs provide robust statistical evidence of the association of a given genetic locus with heart rate, they are only the starting point for detailed follow-up studies to locate the causal variants and genes and gain further insights into the biological mechanisms underlying the observed associations.

Genomewide association study of immune traits in chicken F2 resource population.

Immune traits play pivotal roles in animal immune capacity development and disease resistance. Single nucleotide polymorphisms (SNPs) are common forms of genetic variations among individuals, which are thought to account for the majority of inherited phenotypic variations. In this study, we performed genomewide association, using the Illumina 60K SNP BeadChip studies to detect molecular markers and candidate genes associated with immune traits in an F2 population. Sixteen immune traits were measured. We identified 85 significant SNPs (p < 2.98 × 10(-6) ) with 5% as the genomewide significance threshold, 380 SNPs of suggestive significance (p < 5.96 × 10(-5) ) from simple model (general linear model, GLM) and 15 SNPs of suggestive significance (p < 5.96 × 10(-5) ) from the compressed mixed linear model (MLM), which were also found in GLM (six significant SNPs and seven suggestive SNPs). Three significant SNPs (GGaluGA151406, Gga_rs14554319 and Gga_rs13593979) and candidate genes (LYRM4 and KTN1) were found to be associated with avian influenza antibody titres, and the first two SNPs are from the results of two-model analysis. For the immune organs, through the analysis of GLM, 19 SNPs were found to be significantly associated with the thymus weight, 61 SNPs were significantly associated with the bursa of Fabricius weight, six of which were located within a 34-Mb region (125 846 474-159 649 698 bp) on chicken chromosome 1 (GGA1). A candidate region relevant to haematological traits from GLM was found in GGA4 and 9 loci were located on it. Three loci (GGaluGA348521, Gga_rs16098446 and GGaluGA348518) within 179 kb (16 286 868-16 466 134 bp) on GGAZ from GLM provided evidence that this genomic segment may be relevant to red blood cell volume distribution width (RDW). Our study provides a list of significant SNPs and candidate genes that will be valuable information for unveiling the underlying molecular mechanism of immune regulation.