Validating, augmenting and refining genome-wide association signals

Polygenic risk and hostile environments: Links to stable and dynamic antisocial behaviors across adolescence

Adverse environments are linked to elevated youth antisocial behavior. However, this relation is thought to depend, in part, on genetic susceptibility. The present study investigated whether polygenic risk for antisociality moderates relations between hostile environments and stable as well as dynamic antisocial behaviors across adolescence. We derived two antisocial-linked polygenic risk scores (PRS) (N = 721) based on previous genome-wide association studies. Forms of antisocial behavior (nonaggressive conduct problems, physical aggression, social aggression) and environmental hostility (harsh parenting and school violence) were assessed at age 13, 15, and 17 years. Relations to individual differences stable across adolescence (latent stability) vs. time-specific states (timepoint residual variance) of antisocial behavior were assessed via structural equation models. Higher antisocial PRS, harsh parenting, and school violence were linked to stable elevations in antisocial behaviors across adolescence. We identified a consistent polygenic-environment interaction suggestive of differential susceptibility in late adolescence. At age 17, harsher parenting was linked to higher social aggression in those with higher antisocial PRS, and lower social aggression in those with lower antisocial PRS. This suggests that genetics and environmental hostility relate to stable youth antisocial behaviors, and that genetic susceptibility moderates home environment-antisocial associations specifically in late adolescence.

Phenome-wide association study on miRNA-related sequence variants: the UK Biobank

BACKGROUND

Genetic variants in the coding region could directly affect the structure and expression levels of genes and proteins. However, the importance of variants in the non-coding region, such as microRNAs (miRNAs), remain to be elucidated. Genetic variants in miRNA-related sequences could affect their biogenesis or functionality and ultimately affect disease risk. Yet, their implications and pleiotropic effects on many clinical conditions remain unknown.

METHODS

Here, we utilised genotyping and hospital records data in the UK Biobank (N = 423,419) to investigate associations between 346 genetic variants in miRNA-related sequences and a wide range of clinical diagnoses through phenome-wide association studies. Further, we tested whether changes in blood miRNA expression levels could affect disease risk through colocalisation and Mendelian randomisation analysis.

RESULTS

We identified 122 associations for six variants in the seed region of miRNAs, nine variants in the mature region of miRNAs, and 27 variants in the precursor miRNAs. These included associations with hypertension, dyslipidaemia, immune-related disorders, and others. Nineteen miRNAs were associated with multiple diagnoses, with six of them associated with multiple disease categories. The strongest association was reported between rs4285314 in the precursor of miR-3135b and celiac disease risk (odds ratio (OR) per effect allele increase = 0.37, P = 1.8 × 10-162). Colocalisation and Mendelian randomisation analysis highlighted potential causal role of miR-6891-3p in dyslipidaemia.

CONCLUSIONS

Our study demonstrates the pleiotropic effect of miRNAs and offers insights to their possible clinical importance.

Functional genomics identify causal variant underlying the protective CTSH locus for Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disease, which has a high heritability of up to 79%. Exploring the genetic basis is essential for understanding the pathogenic mechanisms underlying AD development. Recent genome-wide association studies (GWASs) reported an AD-associated signal in the Cathepsin H (CTSH) gene in European populations. However, the exact functional/causal variant(s), and the genetic regulating mechanism of CTSH in AD remain to be determined. In this study, we carried out a comprehensive study to characterize the role of CTSH variants in the pathogenesis of AD. We identified rs2289702 in CTSH as the most significant functional variant that is associated with a protective effect against AD. The genetic association between rs2289702 and AD was validated in independent cohorts of the Han Chinese population. The CTSH mRNA expression level was significantly increased in AD patients and AD animal models, and the protective allele T of rs2289702 was associated with a decreased expression level of CTSH through the disruption of the binding affinity of transcription factors. Human microglia cells with CTSH knockout showed a significantly increased phagocytosis of Aβ peptides. Our study identified CTSH as being involved in AD genetic susceptibility and uncovered the genetic regulating mechanism of CTSH in pathogenesis of AD.

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Information Fragmentation, Encryption and Information Flow in Complex Biological Networks

Assessing where and how information is stored in biological networks (such as neuronal and genetic networks) is a central task both in neuroscience and in molecular genetics, but most available tools focus on the network’s structure as opposed to its function. Here, we introduce a new information-theoretic tool—information fragmentation analysis—that, given full phenotypic data, allows us to localize information in complex networks, determine how fragmented (across multiple nodes of the network) the information is, and assess the level of encryption of that information. Using information fragmentation matrices we can also create information flow graphs that illustrate how information propagates through these networks. We illustrate the use of this tool by analyzing how artificial brains that evolved in silico solve particular tasks, and show how information fragmentation analysis provides deeper insights into how these brains process information and “think”. The measures of information fragmentation and encryption that result from our methods also quantify complexity of information processing in these networks and how this processing complexity differs between primary exposure to sensory data (early in the lifetime) and later routine processing.

Breeding of African sheep reared under low-input/output smallholder production systems for trypanotolerance

Trypanosomiasis is a disease caused by unicellular protozoan parasites. Small ruminants succumb to trypanosomiasis in areas of high tsetse fly challenge, resulting in serious economic loss often to farmers in low-input smallholder systems. At present, trypanosomiasis is treated with trypanocidal drugs, but access to these can be limited, and increasing parasite resistance raises questions about their efficacy. The development of trypanotolerance in small ruminant flocks through targeted breeding strategies is considered a sustainable and economical option for controlling African trypanosomiasis. Recently, quantitative trait loci (QTLs) associated with trypanotolerance traits in sheep have been reported. The results of these studies form the basis for more studies to identify QTLs associated with trypanosomiasis resistance, particularly in African livestock species. For example, signatures of positive selection for trypanotolerance have been identified using genome-wide single-nucleotide polymorphism data. However, there are several challenges in performing genetic analyses using data from low-input smallholder systems, including a lack of recorded pedigree and production records and the need for large sample sizes when flock sizes are often fewer than 50 animals. Breeding strategies to improve trypanotolerance should also preserve existing genetic diversity as well as minimize excessive genetic introgression by trypanosusceptible breeds. This review discusses the possibilities of breeding for trypanosome tolerance/resistance in low-input/low-output small ruminant production systems. Potential challenges are outlined, and potential available genetic resources are described as a foundation for future work.

Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda

A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.

Associating complex traits with genetic variants: polygenic risk scores, pleiotropy and endophenotypes

Genotype-phenotype causal modeling has evolved significantly since Johannsen's and Wright's original designs were published. The development of genomewide assays to interrogate and detect possible causal variants associated with complex traits has expanded the scope of genotype-phenotype research considerably. Clusters of causal variants discovered by genomewide assays and associated with complex traits have been used to develop polygenic risk scores to predict clinical diagnoses of multidimensional human disorders. However, genomewide investigations have met with many challenges to their research designs and statistical complexities which have hindered the reliability and validity of their predictions. Findings linked to differences in heritability estimates between causal clusters and complex traits among unrelated individuals remain a research area of some controversy. Causal models developed from case-control studies as opposed to experiments, as well as other issues concerning the genotype-phenotype causal model and the extent to which various forms of pleiotropy and the concept of the endophenotype add to its complexity, will be reviewed.

Systems genetics analysis of oral squamous cell carcinoma susceptibility using the mouse model: current position and new perspective

Oral squamous cell carcinoma (OSCC) is one of the most common human malignancies with complex etiology and poor prognosis. Although environmental carcinogens and carcinogenic viruses are still considered the main etiologic factors for OSCC development, genetic factors obviously play a key role in the initiation and progression of this neoplasm, given that not all individuals exposed to carcinogens develop the same severity of the disease, if any. Identifying genetic loci modulating OSCC risk may have several important clinical implications, including early detection, prevention and developing new treatment strategies. Due to limitations in controlled and standardized genetic studies in humans, genetic components underlying susceptibility of OSCC development remain largely unknown. A combination of quantitative trait loci mapping in mice, with complementary association studies in humans, has the potential to discover novel cancer risk loci. As of today, a limited number of genetic analyses were applied on rodent models to locate novel genetic loci associated with human OSCC. Here, we discuss the current status of the mouse models use for dissecting the genetic basis of OSCC and highlight how systems genetics analysis using mouse models, may increase our understanding of human OSCC susceptibility.

Systematic review of genome-wide association studies of abdominal aortic aneurysm

BACKGROUND AND AIMS

Abdominal aortic aneurysm (AAA) is an important cause of death worldwide and has an estimated heritability between 70 and 77%. Genome-wide association studies (GWAS) are an established way to discover genetic risk variants. The aim of this study was to systematically review the findings and quality of previous AAA GWAS.

METHODS

The Medline, PubMed, Web of Science and relevant genetic databases were searched to identify previous AAA GWAS. A framework was developed to grade the methodological quality of the GWAS. Data from included studies were extracted to assess methods and findings.

RESULTS

Eight case-control studies were included. Thirty-three of the 38 total single nucleotide polymorphisms (SNPs) previously reported were associated with AAA diagnosis at genome-wide significance (p < 5.0 × 10^-8). The CDKN2B antisense RNA-1 gene had the most significant association with AAA diagnosis (p = 6.94 × 10^-29 and p = 1.54 × 10^-33 for rs4007642 and rs10757274 respectively). Age, sex and smoking history were not reported for the complete cohort in any of the included studies, although five of the eight studies adjusted or matched for at least two confounding variables. All included studies had important design limitations including lack of sample size estimation, inconsistent case and control ascertainment and limited phenotyping of the AAAs. AAA growth was assessed in one GWAS, however, no significant associations with the reported SNPs were found.

CONCLUSIONS

This systematic review identified 33 SNPs associated with AAA diagnosis at genome-wide significance previously validated in multiple cohorts. The association between SNPs and AAA growth was not adequately examined. Previous GWAS have a number of design limitations.

Genetic variants for morningness in relation to habitual sleep-wake behavior and diurnal preference in a population-based sample of 17,243 adults

OBJECTIVE

Associations of eveningness with health hazards benefit from analyzing to what extent the polygenic score for morningness correlates with the assessments of the behavioral trait of morningness-eveningness and chronotype.

METHODS

With a population-based sample of 17,243 Finnish adults, aged 25-74 years, this study examines the associations of four feasible assessment methods of chronotype, a) biological the genetic liability based on the polygenic score for morningness (PGS_morn), b) the widely-used single item for self-assessed morningness/eveningness (MEQ_i19) of the original Morningness-Eveningness Questionnaire (MEQ), c) the behavioral trait of morningness-eveningness as assessed with the score on the shortened version (sMEQ) of the original MEQ, and d) the phase of entrainment as assessed with the habitual midpoint of sleep based on the self-reported sleep-wake schedule during weekend (Sleep_mid-wknd) as well as the sleep debt corrected midpoint of sleep (Sleep_mid-corr).

RESULTS

All self-report measures correlated with each other, but very weakly with the PGS_morn, which explained 1-2% of the variation in diurnal preference or habitual sleep-wake schedule. The influence of age was greater on Sleep_mid-wknd and Sleep_mid-corr than on the sMEQ or MEQ_i19, indicating that the diurnal preference might be a more stable indicator for morningness-eveningness than the sleep-wake schedule. Analyses of the discrepancies between sMEQ and MEQ_i19 indicated that eveningness can be over-estimated when relying on only the single-item self-assessment.

CONCLUSIONS

The current polygenic score for morningness explains only a small proportion of the variation in diurnal preference or habitual sleep-wake schedule. The molecular genetic basis for morningness-eveningness needs further elucidation.

Investigation of gene-gene interactions of clock genes for chronotype in a healthy Korean population

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

Genomic Prediction of (Mal)Adaptation Across Current and Future Climatic Landscapes

Signals of local adaptation have been found in many plants and animals, highlighting the heterogeneity in the distribution of adaptive genetic variation throughout species ranges. In the coming decades, global climate change is expected to induce shifts in the selective pressures that shape this adaptive variation. These changes in selective pressures will likely result in varying degrees of local climate maladaptation and spatial reshuffling of the underlying distributions of adaptive alleles. There is a growing interest in using population genomic data to help predict future disruptions to locally adaptive gene-environment associations. One motivation behind such work is to better understand how the effects of changing climate on populations’ short-term fitness could vary spatially across species ranges. Here we review the current use of genomic data to predict the disruption of local adaptation across current and future climates. After assessing goals and motivationsunderlying the approach, we review the main steps and associated statistical methods currently in use and explore our current understanding of the limits and future potential of using genomics to predict climate change (mal)adaptation.

Identification of novel seed longevity genes related to oxidative stress and seed coat by genome-wide association studies and reverse genetics

Seed longevity is a polygenic trait of relevance for agriculture and for understanding the effect of environment on the ageing of biological systems. In order to identify novel longevity genes, we have phenotyped the natural variation of 270 ecotypes of the model plant, Arabidopsis thaliana, for natural ageing and for three accelerated ageing methods. Genome-wide analysis, using publicly available single-nucleotide polymorphisms (SNPs) data sets, identified multiple genomic regions associated with variation in seed longevity. Reverse genetics of 20 candidate genes in Columbia ecotype resulted in seven genes positive for seed longevity (PSAD1, SSLEA, SSTPR, DHAR1, CYP86A8, MYB47 and SPCH) and five negative ones (RBOHD, RBOHE, RBOHF, KNAT7 and SEP3). In this uniform genetic background, natural and accelerated ageing methods provided similar results for seed-longevity in knock-out mutants. The NADPH oxidases (RBOHs), the dehydroascorbate reductase (DHAR1) and the photosystem I subunit (PSAD1) highlight the important role of oxidative stress on seed ageing. The cytochrome P-450 hydroxylase, CYP86A8, and the transcription factors, MYB47, KNAT7 and SEP3, support the protecting role of the seed coat during seed ageing.

Leveraging genetic ancestry to study health disparities

Research to understand human genomic variation and its implications in health has great potential to contribute in the reduction of health disparities. Biological anthropology can play important roles in genomics and health disparities research using a biocultural approach. This paper argues that racial/ethnic categories should not be used as a surrogate for sociocultural factors or global genomic clusters in biomedical research or clinical settings, because of the high genetic heterogeneity that exists within traditional racial/ethnic groups. Genetic ancestry is used to show variation in ancestral genomic contributions to recently admixed populations in the United States, such as African Americans and Hispanic/Latino Americans. Genetic ancestry estimates are also used to examine the relationship between ancestry‐related biological and sociocultural factors affecting health disparities. To localize areas of genomes that contribute to health disparities, admixture mapping and genome‐wide association studies (GWAS) are often used. Recent GWAS have identified many genetic variants that are highly differentiated among human populations that are associated with disease risk. Some of these are population‐specific variants. Many of these variants may impact disease risk and help explain a portion of the difference in disease burden among racial/ethnic groups. Genetic ancestry is also of particular interest in precision medicine and disparities in drug efficacy and outcomes. By using genetic ancestry, we can learn about potential biological differences that may contribute to the heterogeneity observed across self‐reported racial groups.

Special Issue: Race reconciled II: Interpreting and communicating biological variation and race in 2021

Genome-wide copy number variation-, validation- and screening study implicates a new copy number polymorphism associated with suicide attempts in major depressive disorder

BACKGROUND

The genetic basis of suicide attempts (SA) remains unclear. Especially the role of copy number variations (CNVs) remains to be elucidated. The present study aimed to identify susceptibility variants associated with SA among Chinese with major depressive disorder (MDD), covering both CNVs and single-nucleotide polymorphisms (SNPs).

METHODS

We conducted a genome-wide association study (GWAS) on MDD patients with and without SA and top results were tested in a replication study. A genome-wide CNV study was also performed. Subsequently, a validation assay using qRT-PCR technology was performed to confirm any associated CNVs and then applied to the entire cohort to examine the association.

RESULTS

Although GWAS did not identify any SNPs reaching genome-wide significance, we identified TPH2 as the top susceptibility gene (p-value = 2.75e-05) in gene-based analysis, which is a strong biological candidate for its role in the serotonergic system. As for CNV analysis, we found that the global rate of CNV was higher in SA than that in non-SA subjects (p-value = 0.023). Genome-wide CNV study revealed an SA-associated CNV region that achieved genome-wide significance (corrected p-value = 0.014). The associated CNV was successfully validated with a more rigorous qRT-PCR assay and identified to be a common variant in this cohort. Its deletion rate was higher in SA subjects [OR = 2.05 (1.02-4.12), adjusted p-value = 0.045]. Based on the GTEx database, genetic variants that probed this CNV were significantly associated with the expression level of ZNF33B in two brain regions (p-value < 4.2e-05). In stratified analysis, the CNV showed a significant effect [OR = 2.58 (1.06-6.27), p-value = 0.039] in those with high neuroticism but not in those with average or low neuroticism.

CONCLUSIONS

We identified a new common CNV likely involved in the etiology of SA. This finding sheds light on an important role of common CNVs in the pathophysiology of SA, suggesting a new promising avenue for investigating its genetic architecture.

Common Genetic Variations Associated with the Persistence of Immunity following Childhood Immunization

Vaccines have revolutionized public health, preventing millions of deaths each year, particularly in childhood. Yet, there is considerable variability in the magnitude and persistence of vaccine-induced immunity. Maintenance of specific antibody is essential for continuity of vaccine-induced serological protection. We conducted a genome-wide association study into the persistence of immunity to three childhood vaccines: capsular group C meningococcal (MenC), Haemophilus influenzae type b, and tetanus toxoid (TT) vaccines. We detail associations between variants in a locus containing a family of signal-regulatory proteins and the persistence MenC immunity. We postulate a regulatory role for the lead SNP, with supporting epigenetic and expression quantitative trait loci data. Furthermore, we define associations between SNPs in the human leukocyte antigen (HLA) locus and the persistence of TT-specific immunity. Moreover, we describe four classical HLA alleles, HLA DRB1^∗0301, HLA DQB1^∗0201, HLA DQB1^∗0602, and HLA DRB1^∗1501, associated with TT-specific immunity, independent of the lead SNP association.

Identification and validation of a novel candidate gene regulating net meat weight in Simmental beef cattle based on imputed next-generation sequencing

Objectives

Genome‐wide association studies (GWAS) represent a powerful approach to detecting candidate genes for economically important traits in livestock. Our aim was to identify promising candidate muscle development genes that affect net meat weight (NMW) and validate these candidate genes in cattle.

Materials and methods

Using a next‐generation sequencing (NGS) dataset, we applied ~ 12 million imputed single nucleotide polymorphisms (SNPs) from 1,252 Simmental cattle to detect genes influencing net meat yield by way of a linear mixed model method. Haplotype and linkage disequilibrium (LD) blocks were employed to augment support for identified genes. To investigate the role of MTPN in bovine muscle development, we isolated myoblasts from the longissimus dorsi of a bovine foetus and treated the cells during proliferation, differentiation and hypertrophy.

Results

We identified one SNP (rs100670823) that exceeded our stringent significance threshold (P = 8.58 × 10⁻⁸) for a putative NMW‐related quantitative trait locus (QTL). We identified a promising candidate gene, myotrophin (MTPN), in the region around this SNP Myotrophin had a stimulatory effect on six muscle‐related markers that regulate differentiation and myoblast fusion. During hypertrophy, myotrophin promoted myotube hypertrophy and increased myotube diameters. Cell viability assay and flow cytometry showed that myotrophin inhibited myoblast proliferation.

Conclusions

The present experiments showed that myotrophin increases differentiation and hypertrophy of skeletal muscle cells, while inhibiting their proliferation. Our examination of GWAS results with in vitro biological studies provides new information regarding the potential application of myotrophin to increase meat yields in cattle and helpful information for further studies.

Natural Variation in Portuguese Common Bean Germplasm Reveals New Sources of Resistance Against Fusarium oxysporum f. sp. phaseoli and Resistance-Associated Candidate Genes

Common bean (Phaseolus vulgaris) is one of the most consumed legume crops in the world, and Fusarium wilt, caused by the fungus Fusarium oxysporum f. sp. phaseoli, is one of the major diseases affecting its production. Portugal holds a very promising common bean germplasm with an admixed genetic background that may reveal novel genetic resistance combinations between the original Andean and Mesoamerican gene pools. To identify new sources of Fusarium wilt resistance and detect resistance-associated single-nucleotide polymorphisms (SNPs), we explored, for the first time, a diverse collection of the underused Portuguese common bean germplasm by using genome-wide association analyses. The collection was evaluated for Fusarium wilt resistance under growth chamber conditions, with the highly virulent F. oxysporum f. sp. phaseoli strain FOP-SP1 race 6. Fourteen of the 162 Portuguese accessions evaluated were highly resistant and 71 intermediate. The same collection was genotyped with DNA sequencing arrays, and SNP-resistance associations were tested via a mixed linear model accounting for the genetic relatedness between accessions. The results from the association mapping revealed nine SNPs associated with resistance on chromosomes Pv04, Pv05, Pv07, and Pv08, indicating that Fusarium wilt resistance is under oligogenic control. Putative candidate genes related to phytoalexin biosynthesis, hypersensitive response, and plant primary metabolism were identified. The results reported here highlight the importance of exploring underused germplasm for new sources of resistance and provide new genomic targets for the development of functional markers to support selection in future disease resistance breeding programs.

Role of Tmem163 in zinc-regulated insulin storage of MIN6 cells: Functional exploration of an Indian type 2 diabetes GWAS associated gene

Genome wide association study for type 2 diabetes discovered TMEM163 as a risk locus. Perturbations in TMEM163 expression was reported to be associated with impaired intracellular zinc homeostasis. Physiological concentration of zinc is instrumental to maintain insulin storage and functionality in pancreatic β cells. We found abundant TMEM163 expression in human pancreas, both at transcriptional and translational levels. Knockdown of endogenous Tmem163 in MIN6 cells resulted in increased intracellular zinc and total insulin content, coupled with compromised insulin secretion at high glucose stimuli. Furthermore, Tmem163 knockdown led to enhanced cellular glucose uptake. Upon next generation sequencing, one-third of the studied T2D patients were found to have a novel missense variant in TMEM163 gene. Study participants harboring this missense variant displayed a trend of higher glycemic indices. This is the first report on exploring the biological role of TMEM163 in relation to T2D pathophysiology.

LINC01149 variant modulates MICA expression that facilitates hepatitis B virus spontaneous recovery but increases hepatocellular carcinoma risk

Interpreting disease-causing variants, especially in noncoding regions by genome-wide association studies (GWAS), has become one of the most challenging and demanding tasks. We hypothesized that functional lncRNAs variants in GWAS-identified loci might alter expression level of genes associated with persistent HBV infection and hepatocellular carcinoma (HCC). Integrated bioinformatics approaches were used to prioritize potentially functional variants and a two-stage case-control study (2473 HBV positive HCC patients, 2248 persistent HBV carriers and 2294 spontaneously recovered subjects) was performed to assess the roles of these variants. The rs2844512 G > C variant in LINC01149 was identified to facilitate HBV spontaneous recovery (OR = 0.84, 95% CI = 0.77-0.92) but increase the risk of HCC (OR = 1.21, 95% CI = 1.11-1.32) in combined samples. Subsequent biological assays indicated this variant created a binding site for miR-128-3p and upregulated MICA expression by serving as a miRNA sponge, which might recruit NK-cells to lyse infected cells, but release highly soluble MICA by shedding to induce NK-cells exhaustion and tumor immune evasion. These findings highlight a regulatory circuit between LINC01149 and MICA, mediating by miR-128-3p, and the important role of upregulated MICA in conferring susceptibility to persistent HBV infection and HCC.

Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale

BACKGROUND

Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv).

RESULTS

Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively.

CONCLUSIONS

Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

Power, false discovery rate and Winner's Curse in eQTL studies

Investigation of the genetic architecture of gene expression traits has aided interpretation of disease and trait-associated genetic variants; however, key aspects of expression quantitative trait loci (eQTL) study design and analysis remain understudied. We used extensive, empirically driven simulations to explore eQTL study design and the performance of various analysis strategies. Across multiple testing correction methods, false discoveries of genes with eQTLs (eGenes) were substantially inflated when false discovery rate (FDR) control was applied to all tests and only appropriately controlled using hierarchical procedures. All multiple testing correction procedures had low power and inflated FDR for eGenes whose causal SNPs had small allele frequencies using small sample sizes (e.g. frequency <10% in 100 samples), indicating that even moderately low frequency eQTL SNPs (eSNPs) in these studies are enriched for false discoveries. In scenarios with ≥80% power, the top eSNP was the true simulated eSNP 90% of the time, but substantially less frequently for very common eSNPs (minor allele frequencies >25%). Overestimation of eQTL effect sizes, so-called ‘Winner’s Curse’, was common in low and moderate power settings. To address this, we developed a bootstrap method (BootstrapQTL) that led to more accurate effect size estimation. These insights provide a foundation for future eQTL studies, especially those with sampling constraints and subtly different conditions.

Genomic prediction offers the most effective marker assisted breeding approach for ability to prevent arsenic accumulation in rice grains

The high concentration of arsenic (As) in rice grains, in a large proportion of the rice growing areas, is a critical issue. This study explores the feasibility of conventional (QTL-based) marker-assisted selection and genomic selection to improve the ability of rice to prevent As uptake and accumulation in the edible grains. A japonica diversity panel (RP) of 228 accessions phenotyped for As concentration in the flag leaf (FL-As) and in the dehulled grain (CG-As), and genotyped at 22,370 SNP loci, was used to map QTLs by association analysis (GWAS) and to train genomic prediction models. Similar phenotypic and genotypic data from 95 advanced breeding lines (VP) with japonica genetic backgrounds, was used to validate related QTLs mapped in the RP through GWAS and to evaluate the predictive ability of across populations (RP-VP) genomic estimate of breeding value (GEBV) for As exclusion. Several QTLs for FL-As and CG-As with a low-medium individual effect were detected in the RP, of which some colocalized with known QTLs and candidate genes. However, less than 10% of those QTLs could be validated in the VP without loosening colocalization parameters. Conversely, the average predictive ability of across populations GEBV was rather high, 0.43 for FL-As and 0.48 for CG-As, ensuring genetic gains per time unit close to phenotypic selection. The implications of the limited robustness of the GWAS results and the rather high predictive ability of genomic prediction are discussed for breeding rice for significantly low arsenic uptake and accumulation in the edible grains.

Cross-Cancer Pleiotropic Associations with Lung Cancer Risk in African Americans

BACKGROUND

Identifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans.

METHODS

We conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status.

RESULTS

We identified three novel genomic regions significantly associated (FDR-corrected P <0.10) with lung cancer risk (rs336958 on 5q14.3, rs7186207 on 16q22.2, and rs11658063 on 17q12). On chromosome16q22.2, rs7186207 was significantly associated with reduced risk [OR = 0.43; 95% confidence interval (CI), 0.73-0.89], and functional annotation using GTEx showed rs7186207 modifies DHODH gene expression. The minor allele at rs336958 on 5q14.3 was associated with increased lung cancer risk (OR = 1.47; 95% CI, 1.22-1.78), whereas the minor allele at rs11658063 on 17q12 was associated with reduced risk (OR = 0.80; 95% CI, 0.72-0.90).

CONCLUSIONS

We identified novel associations on chromosomes 5q14.3, 16q22.2, and 17q12, which contain HNF1B, DHODH, and HAPLN1 genes, respectively. SNPs within these regions have been previously associated with multiple cancers. This is the first study to examine cross-cancer pleiotropic associations for lung cancer in African Americans.

IMPACT

Our findings demonstrate novel cross-cancer pleiotropic associations with lung cancer risk in African Americans.

Trypsin-encoding PRSS1-PRSS2 variations influence the risk of asparaginase-associated pancreatitis in children with acute lymphoblastic leukemia: a Ponte di Legno toxicity working group report

Asparaginase-associated pancreatitis is a life-threatening toxicity to childhood acute lymphoblastic leukemia treatment. To elucidate genetic predisposition and asparaginase-associated pancreatitis pathogenesis, ten trial groups contributed remission samples from patients aged 1.0-17.9 years treated for acute lymphoblastic leukemia between 2000 and 2016. Cases (n=244) were defined by the presence of at least two of the following criteria: (i) abdominal pain; (ii) levels of pancreatic enzymes ≥3 × upper normal limit; and (iii) imaging compatible with pancreatitis. Controls (n=1320) completed intended asparaginase therapy, with 78% receiving ≥8 injections of pegylated-asparaginase, without developing asparaginase-associated pancreatitis. rs62228256 on 20q13.2 showed the strongest association with the development of asparaginase-associated pancreatitis (odds ratio=3.75; P=5.2×10-8). Moreover, rs13228878 (OR=0.61; P=7.1×10-6) and rs10273639 (OR=0.62; P=1.1×10-5) on 7q34 showed significant association with the risk of asparaginase-associated pancreatitis. A Dana Farber Cancer Institute ALL Consortium cohort consisting of patients treated on protocols between 1987 and 2004 (controls=285, cases=33), and the Children's Oncology Group AALL0232 cohort (controls=2653, cases=76) were available as replication cohorts for the 20q13.2 and 7q34 variants, respectively. While rs62228256 was not validated as a risk factor (P=0.77), both rs13228878 (P=0.03) and rs10273639 (P=0.04) were. rs13228878 and rs10273639 are in high linkage disequilibrium (r2=0.94) and associated with elevated expression of the PRSS1 gene, which encodes for trypsinogen, and are known risk variants for alcohol-associated and sporadic pancreatitis in adults. Intra-pancreatic trypsinogen cleavage to proteolytic trypsin induces autodigestion and pancreatitis. In conclusion, this study finds a shared genetic predisposition between asparaginase-associated pancreatitis and non-asparaginase-associated pancreatitis, and targeting the trypsinogen activation pathway may enable identification of effective interventions for asparaginase-associated pancreatitis.

A Case of Need: Linking Traits to Genebank Accessions

Genebanks are responsible for collecting, maintaining, characterizing, documenting, and distributing plant genetic resources for research, education, and breeding purposes. The rationale for requests of plant materials varies highly from areas of anthropology, social science, small-holder farmers, the commercial sector, rehabilitation of degraded systems, all the way to crop improvement and basic research. Matching "the right" accessions to a particular request is not always a straightforward process especially when genetic resource collections are large and the user does not already know which accession or even which species they want to study. Some requestors have limited knowledge of the crop; therefore, they do not know where to begin and thus, initiate the search by consultation with crop curators to help direct their request to the most suitable germplasm. One way to enhance the use of genebank material and aid in the selection of genetic resources is to have thoroughly cataloged agronomic, biochemical, genomic, and other traits linked to genebank accessions. In general, traits of importance to most users include genotypes that thrive under various biotic and abiotic stresses, morphological traits (color, shape, size of fruits), plant architecture, disease resistance, nutrient content, yield, and crop specific quality traits. In this review, we discuss methods for linking traits to genebank accessions, examples of linked traits, and some of the complexities involved, while reinforcing why it is critical to have well characterized accessions with clear trait data publicly available.

Identifying the genetic risk factors for treatment response to lurasidone by genome-wide association study: A meta-analysis of samples from three independent clinical trials

A genome-wide association study (GWAS) of response of schizophrenia patients to the atypical antipsychotic drug, lurasidone, based on two double-blind registration trials, identified SNPs from four classes of genes as predictors of efficacy, but none were genome wide significant (GWS). After inclusion of data from a third lurasidone trial, meta-analysis identified a GWS marker and other findings consistent with our first study. The primary end-point was change in Total Positive and Negative Syndrome Scale (PANSS) between baseline and last observation carried forward. rs4736253, a genetic locus near KCNK9, encoding the K_2P9.1 potassium channel, with a role in cognition and neurodevelopment, was the top marker in patients of European ancestry (EUR) (n = 264), reaching GWS (p = 4.78 × 10^-8). rs10180106 (p = 4.92 × 10^-7), located at an intron region of CTNNA2, a SCZ risk gene important for dendritic spine stabilization, was one of other best response markers for EUR patients. SNPs at STXBP5L (rs511841, p = 2.63 × 10^-7) were the top markers for patients of African ancestry (n = 158). The association between PTPRD, NRG1, and MAGI1 previously reported to be related to response to lurasidone in the first two trials, showed a trend of significant association in the third trial. None of these genetic loci showed significant associations with clinical response in the corresponding placebo groups (n = 107 for EUR; n = 58 for AFR). This meta-analysis yielded the first GWAS-based GWS biomarker for lurasidone response and additional support for the conclusion that genes related to synaptic biology and/or risk for SCZ are the strongest predictors of response to lurasidone in schizophrenia patients.

Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort

BACKGROUND

Common variants have explained less than the amount of heritability expected for complex diseases, which has led to interest in less-common variants and more powerful approaches to the analysis of whole-genome scans. Because of low frequency (low statistical power), less-common variants are best analyzed using SNP-set methods such as gene-set or pathway-based analyses. However, there is as yet no clear consensus regarding how to focus in on potential risk variants following set-based analyses. We used a stepwise, telescoping approach to analyze common- and rare-variant data from the Illumina Metabochip array to assess genomic association with colorectal cancer (CRC) in the Japanese sub-population of the Multiethnic Cohort (676 cases, 7180 controls). We started with pathway analysis of SNPs that are in genes and pathways having known mechanistic roles in colorectal cancer, then focused on genes within the pathways that evidenced association with CRC, and finally assessed individual SNPs within the genes that evidenced association. Pathway SNPs downloaded from the dbSNP database were cross-matched with Metabochip SNPs and analyzed using the logistic kernel machine regression approach (logistic SNP-set kernel-machine association test, or sequence kernel association test; SKAT) and related methods.

RESULTS

The TGF-β and WNT pathways were associated with all CRC, and the WNT pathway was associated with colon cancer. Individual genes demonstrating the strongest associations were TGFBR2 in the TGF-β pathway and SMAD7 (which is involved in both the TGF-β and WNT pathways). As partial validation of our approach, a known CRC risk variant in SMAD7 (in both the TGF-β and WNT pathways: rs11874392) was associated with CRC risk in our data. We also detected two novel candidate CRC risk variants (rs13075948 and rs17025857) in TGFBR2, a gene known to be associated with CRC risk.

CONCLUSIONS

A stepwise, telescoping approach identified some potentially novel risk variants associated with colorectal cancer, so it may be a useful method for following up on results of set-based SNP analyses. Further work is required to assess the statistical characteristics of the approach, and additional applications should aid in better clarifying its utility.

Complex polymorphisms in endocytosis genes suggest alpha-cyclodextrin as a treatment for breast cancer

Most breast cancer deaths are caused by metastasis and treatment options beyond radiation and cytotoxic drugs, which have severe side effects, and hormonal treatments, which are or become ineffective for many patients, are urgently needed. This study reanalyzed existing data from three genome-wide association studies (GWAS) using a novel computational biostatistics approach (muGWAS), which had been validated in studies of 600-2000 subjects in epilepsy and autism. MuGWAS jointly analyzes several neighboring single nucleotide polymorphisms while incorporating knowledge about genetics of heritable diseases into the statistical method and about GWAS into the rules for determining adaptive genome-wide significance. Results from three independent GWAS of 1000-2000 subjects each, which were made available under the National Institute of Health's "Up For A Challenge" (U4C) project, not only confirmed cell-cycle control and receptor/AKT signaling, but, for the first time in breast cancer GWAS, also consistently identified many genes involved in endo-/exocytosis (EEC), most of which had already been observed in functional and expression studies of breast cancer. In particular, the findings include genes that translocate (ATP8A1, ATP8B1, ANO4, ABCA1) and metabolize (AGPAT3, AGPAT4, DGKQ, LPPR1) phospholipids entering the phosphatidylinositol cycle, which controls EEC. These novel findings suggest scavenging phospholipids as a novel intervention to control local spread of cancer, packaging of exosomes (which prepare distant microenvironment for organ-specific metastases), and endocytosis of β1 integrins (which are required for spread of metastatic phenotype and mesenchymal migration of tumor cells). Beta-cyclodextrins (βCD) have already been shown to be effective in in vitro and animal studies of breast cancer, but exhibits cholesterol-related ototoxicity. The smaller alpha-cyclodextrins (αCD) also scavenges phospholipids, but cannot fit cholesterol. An in-vitro study presented here confirms hydroxypropyl (HP)-αCD to be twice as effective as HPβCD against migration of human cells of both receptor negative and estrogen-receptor positive breast cancer. If the previous successful animal studies with βCDs are replicated with the safer and more effective αCDs, clinical trials of adjuvant treatment with αCDs are warranted. Ultimately, all breast cancer are expected to benefit from treatment with HPαCD, but women with triple-negative breast cancer (TNBC) will benefit most, because they have fewer treatment options and their cancer advances more aggressively.

Success and failure in replication of genotype-phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations?

Recent developments in sequencing technologies have facilitated genomewide mapping of phenotypic variation in natural populations. Such mapping efforts face a number of challenges potentially leading to low reproducibility. However, reproducible research forms the basis of scientific progress. We here discuss the options for replication and the reasons for potential nonreproducibility. We then review the evidence for reproducible quantitative trait loci (QTL) with a focus on natural animal populations. Existing case studies of replication fall into three categories: (i) traits that have been mapped to major effect loci (including chromosomal inversion and supergenes) by independent research teams; (ii) QTL fine-mapped in discovery populations; and (iii) attempts to replicate QTL across multiple populations. Major effect loci, in particular those associated with inversions, have been successfully replicated in several cases within and across populations. Beyond such major effect variants, replication has been more successful within than across populations, suggesting that QTL discovered in natural populations may often be population-specific. This suggests that biological causes (differences in linkage patterns, allele frequencies or context-dependencies of QTL) contribute to nonreproducibility. Evidence from other fields, notably animal breeding and QTL mapping in humans, suggests that a significant fraction of QTL is indeed reproducible in direction and magnitude at least within populations. However, there is also a large number of QTL that cannot be easily reproduced. We put forward that more studies should explicitly address the causes and context-dependencies of QTL signals, in particular to disentangle linkage differences, allele frequency differences and gene-by-environment interactions as biological causes of nonreproducibility of QTL, especially between populations.

A Decade of GWAS Results in Lung Cancer

Genome-wide association studies (GWAS) were successful to identify genetic factors robustly associated with lung cancer. This review aims to synthesize the literature in this field and accelerate the translation of GWAS discoveries into results that are closer to clinical applications. A chronologic presentation of published GWAS on lung cancer susceptibility, survival, and response to treatment is presented. The most important results are tabulated to provide a concise overview in one read. GWAS have reported 45 lung cancer susceptibility loci with varying strength of evidence and highlighted suspected causal genes at each locus. Some genetic risk loci have been refined to more homogeneous subgroups of lung cancer patients in terms of histologic subtypes, smoking status, gender, and ethnicity. Overall, these discoveries are an important step for future development of new therapeutic targets and biomarkers to personalize and improve the quality of care for patients. GWAS results are on the edge of offering new tools for targeted screening in high-risk individuals, but more research is needed if GWAS are to pay off the investment. Complementary genomic datasets and functional studies are needed to refine the underlying molecular mechanisms of lung cancer preliminarily revealed by GWAS and reach results that are medically actionable. Cancer Epidemiol Biomarkers Prev; 27(4); 363-79. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Validating genome-wide associated signals for clinical mastitis in German Holstein cattle

A validation study for six genomic regions previously identified by a genome-wide association study for somatic cell score was conducted with data of clinical mastitis in German Holstein cattle. Out of 10 tested SNPs, five on chromosomes 6, 13 and 19 were significantly associated with clinical mastitis (P < 0.05). Three SNPs on chromosomes 6 and 19 had the same direction of effect as those previously reported in the initial genome-wide association study for somatic cell score. The other two SNPs on chromosome 13 had opposite effects. As well as validating associations within known QTL from previous studies, e.g. chromosomes 6 and 19, novel loci on chromosome 13 were confirmed. Promising candidate genes are, for example: deoxycytidine kinase, immunoglobulin J chain, vitamin D binding protein, forkhead box K2, sodium/hydrogen exchanger 8 and cytoplasmic nuclear factor of activated T-cells 2. Our confirmation study provides additional evidence for the functional role of the linked genomic regions to immune response. This information can be used as a basis for further functional studies for those potential genes.

How often should we expect to be wrong? Statistical power, P values, and the expected prevalence of false discoveries

There is a clear perception in the literature that there is a crisis in reproducibility in the biomedical sciences. Many underlying factors contributing to the prevalence of irreproducible results have been highlighted with a focus on poor design and execution of experiments along with the misuse of statistics. While these factors certainly contribute to irreproducibility, relatively little attention outside of the specialized statistical literature has focused on the expected prevalence of false discoveries under idealized circumstances. In other words, when everything is done correctly, how often should we expect to be wrong? Using a simple simulation of an idealized experiment, it is possible to show the central role of sample size and the related quantity of statistical power in determining the false discovery rate, and in accurate estimation of effect size. According to our calculations, based on current practice many subfields of biomedical science may expect their discoveries to be false at least 25% of the time, and the only viable course to correct this is to require the reporting of statistical power and a minimum of 80% power (1 - β = 0.80) for all studies.

Efficient estimation of disease odds ratios for follow-up genetic association studies

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, "GFcom", implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

Ankyrin-G isoform imbalance and interneuronopathy link epilepsy and bipolar disorder

ANK3, encoding the adaptor protein Ankyrin-G (AnkG), has been implicated in bipolar disorder by genome-wide association studies. ANK3 has multiple alternative first exons, and a bipolar disorder-associated ANK3 variant has been shown to reduce the expression of exon 1b. Here we identify mechanisms through which reduced ANK3 exon 1b isoform expression disrupts neuronal excitation-inhibition balance. We find that parvalbumin (PV) interneurons and principal cells differentially express ANK3 first exon subtypes. PV interneurons express only isoforms containing exon 1b, whereas excitatory principal cells express exon 1e alone or both 1e and 1b. In transgenic mice deficient for exon 1b, PV interneurons lack voltage-gated sodium channels at their axonal initial segments and have increased firing thresholds and diminished action potential dynamic range. These mice exhibit an Ank3 gene dosage-dependent phenotype including behavior changes modeling bipolar disorder, epilepsy and sudden death. Thus ANK3's important association with human bipolar susceptibility may arise from imbalance between AnkG function in interneurons and principal cells and resultant excessive circuit sensitivity and output. AnkG isoform imbalance is a novel molecular endophenotype and potential therapeutic target.

Genome-wide association study of sepsis in extremely premature infants

OBJECTIVE

To identify genetic variants associated with sepsis (early-onset and late-onset) using a genome-wide association (GWA) analysis in a cohort of extremely premature infants.

STUDY DESIGN

Previously generated GWA data from the Neonatal Research Network's anonymised genomic database biorepository of extremely premature infants were used for this study. Sepsis was defined as culture-positive early-onset or late-onset sepsis or culture-proven meningitis. Genomic and whole-genome-amplified DNA was genotyped for 1.2 million single-nucleotide polymorphisms (SNPs); 91% of SNPs were successfully genotyped. We imputed 7.2 million additional SNPs. p Values and false discovery rates (FDRs) were calculated from multivariate logistic regression analysis adjusting for gender, gestational age and ancestry. Target statistical value was p<10-5. Secondary analyses assessed associations of SNPs with pathogen type. Pathway analyses were also run on primary and secondary end points.

RESULTS

Data from 757 extremely premature infants were included: 351 infants with sepsis and 406 infants without sepsis. No SNPs reached genome-wide significance levels (5×10-8); two SNPs in proximity to FOXC2 and FOXL1 genes achieved target levels of significance. In secondary analyses, SNPs for ELMO1, IRAK2 (Gram-positive sepsis), RALA, IMMP2L (Gram-negative sepsis) and PIEZO2 (fungal sepsis) met target significance levels. Pathways associated with sepsis and Gram-negative sepsis included gap junctions, fibroblast growth factor receptors, regulators of cell division and interleukin-1-associated receptor kinase 2 (p values<0.001 and FDR<20%).

CONCLUSIONS

No SNPs met genome-wide significance in this cohort of extremely low birthweight infants; however, areas of potential association and pathways meriting further study were identified.

Using Zebrafish to Test the Genetic Basis of Human Craniofacial Diseases

Genome-wide association studies (GWASs) opened an innovative and productive avenue to investigate the molecular basis of human craniofacial disease. However, GWASs identify candidate genes only; they do not prove that any particular one is the functional villain underlying disease or just an unlucky genomic bystander. Genetic manipulation of animal models is the best approach to reveal which genetic loci identified from human GWASs are functionally related to specific diseases. The purpose of this review is to discuss the potential of zebrafish to resolve which candidate genetic loci are mechanistic drivers of craniofacial diseases. Many anatomic, embryonic, and genetic features of craniofacial development are conserved among zebrafish and mammals, making zebrafish a good model of craniofacial diseases. Also, the ability to manipulate gene function in zebrafish was greatly expanded over the past 20 y, enabling systems such as Gateway Tol2 and CRISPR-Cas9 to test gain- and loss-of-function alleles identified from human GWASs in coding and noncoding regions of DNA. With the optimization of genetic editing methods, large numbers of candidate genes can be efficiently interrogated. Finding the functional villains that underlie diseases will permit new treatments and prevention strategies and will increase understanding of how gene pathways operate during normal development.

Genome-wide meta-analysis identifies a novel susceptibility signal at CACNA2D3 for nicotine dependence

Nicotine dependence (ND) has a reported heritability of 40-70%. Low-coverage whole-genome sequencing was conducted in 1,889 samples from the UCSF Family study. Linear mixed models were used to conduct genome-wide association (GWA) tests of ND in this and five cohorts obtained from the database of Genotypes and Phenotypes. Fixed-effect meta-analysis was carried out separately for European (n = 14,713) and African (n = 3,369) participants, and then in a combined analysis of both ancestral groups. The meta-analysis of African participants identified a significant and novel susceptibility signal (rs56247223; p = 4.11 × 10^-8 ). Data from the Genotype-Tissue Expression (GTEx) study suggested the protective allele is associated with reduced mRNA expression of CACNA2D3 in three human brain tissues (p < 4.94 × 10^-2 ). Sequence data from the UCSF Family study suggested that a rare nonsynonymous variant in this gene conferred increased risk for ND (p = 0.01) providing further support for CACNA2D3 involvement in ND. Suggestive associations were observed in six additional regions in both European and merged populations (p < 5.00 × 10^-6 ). The top variants were found to regulate mRNA expression levels of genes in human brains using GTEx data (p < 0.05): HAX1 and CHRNB2 (rs1760803), ADAMTSL1 (rs17198023), PEX2 (rs12680810), GLIS3 (rs12348139), non-coding RNA for LINC00476 (rs10759883), and GABBR1 (rs56020557 and rs62392942). A gene-based association test further supported the relation between GABBR1 and ND (p = 6.36 × 10^-7 ). These findings will inform the biological mechanisms and development of therapeutic targets for ND.

The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping

Susceptibility to rheumatic diseases, such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, juvenile idiopathic arthritis and psoriatic arthritis, includes a large genetic component. Understanding how an individual's genetic background influences disease onset and outcome can lead to a better understanding of disease biology, improved diagnosis and treatment, and, ultimately, to disease prevention or cure. The past decade has seen great progress in the identification of genetic variants that influence the risk of rheumatic diseases. The challenging task of unravelling the function of these variants is ongoing. In this Review, the major insights from genetic studies, gained from advances in technology, bioinformatics and study design, are discussed in the context of rheumatic disease. In addition, pivotal genetic studies in the main rheumatic diseases are highlighted, with insights into how these studies have changed the way we view these conditions in terms of disease overlap, pathways of disease and potential new therapeutic targets. Finally, the limitations of genetic studies, gaps in our knowledge and ways in which current genetic knowledge can be fully translated into clinical benefit are examined.

Common coding variant in SERPINA1 increases the risk for large artery stroke

Large artery atherosclerotic stroke (LAS) shows substantial heritability not explained by previous genome-wide association studies. Here, we explore the role of coding variation in LAS by analyzing variants on the HumanExome BeadChip in a total of 3,127 cases and 9,778 controls from Europe, Australia, and South Asia. We report on a nonsynonymous single-nucleotide variant in serpin family A member 1 (SERPINA1) encoding alpha-1 antitrypsin [AAT; p.V213A; P = 5.99E-9, odds ratio (OR) = 1.22] and confirm histone deacetylase 9 (HDAC9) as a major risk gene for LAS with an association in the 3'-UTR (rs2023938; P = 7.76E-7, OR = 1.28). Using quantitative microscale thermophoresis, we show that M1 (A213) exhibits an almost twofold lower dissociation constant with its primary target human neutrophil elastase (NE) in lipoprotein-containing plasma, but not in lipid-free plasma. Hydrogen/deuterium exchange combined with mass spectrometry further revealed a significant difference in the global flexibility of the two variants. The observed stronger interaction with lipoproteins in plasma and reduced global flexibility of the Val-213 variant most likely improve its local availability and reduce the extent of proteolytic inactivation by other proteases in atherosclerotic plaques. Our results indicate that the interplay between AAT, NE, and lipoprotein particles is modulated by the gate region around position 213 in AAT, far away from the unaltered reactive center loop (357-360). Collectively, our findings point to a functionally relevant balance between lipoproteins, proteases, and AAT in atherosclerosis.

Drosophila and genome-wide association studies: a review and resource for the functional dissection of human complex traits

Human genome-wide association studies (GWAS) have successfully identified thousands of susceptibility loci for common diseases with complex genetic etiologies. Although the susceptibility variants identified by GWAS usually have only modest effects on individual disease risk, they contribute to a substantial burden of trait variation in the overall population. GWAS also offer valuable clues to disease mechanisms that have long proven to be elusive. These insights could lead the way to breakthrough treatments; however, several challenges hinder progress, making innovative approaches to accelerate the follow-up of results from GWAS an urgent priority. Here, we discuss the largely untapped potential of the fruit fly, Drosophila melanogaster, for functional investigation of findings from human GWAS. We highlight selected examples where strong genomic conservation with humans along with the rapid and powerful genetic tools available for flies have already facilitated fine mapping of association signals, elucidated gene mechanisms, and revealed novel disease-relevant biology. We emphasize current research opportunities in this rapidly advancing field, and present bioinformatic analyses that systematically explore the applicability of Drosophila for interrogation of susceptibility signals implicated in more than 1000 human traits, based on all GWAS completed to date. Thus, our discussion is targeted at both human geneticists seeking innovative strategies for experimental validation of findings from GWAS, as well as the Drosophila research community, by whom ongoing investigations of the implicated genes will powerfully inform our understanding of human disease.

A genome-wide investigation into parent-of-origin effects in autism spectrum disorder identifies previously associated genes including SHANK3

Autism spectrum disorder (ASD) is known to be a heritable neurodevelopmental disorder affecting more than 1% of the population but in the majority of ASD cases, the genetic cause has not been identified. Parent-of-origin effects have been highlighted as an important mechanism in the pathology of neurodevelopmental disorders such as Prader-Willi and Angelman syndrome, with individuals with these syndromes often exhibiting ASD symptoms. Consequently, systematic investigation of these effects in ASD is clearly an important line of investigation in elucidating the underlying genetic mechanisms. Using estimation of maternal, imprinting and interaction effects using multinomial modelling (EMIM), we simultaneously investigated imprinting, maternal genetic effects and associations in the Autism Genome Project and Simons Simplex Consortium genome-wide association data sets. To avoid using the overly stringent genome-wide association study significance level, we used a Bayesian threshold that takes into account the sample size, allele frequency and any available prior knowledge. Between the two data sets, we identified a total of 18 imprinting effects and 68 maternal genetic effects that met this Bayesian threshold criteria, but none met the threshold in both data sets. We identified imprinting and maternal genetic effects for regions that have previously shown evidence for parent-of-origin effects in ASD. Together with these findings, we have identified maternal genetic effects not previously identified in ASD at a locus in SHANK3 on chromosome 22 and a locus in WBSCR17 on chromosome 7 (associated with Williams syndrome). Both genes have previously been associated with ASD.

Validating Genome-Wide Association Candidates Controlling Quantitative Variation in Nodulation

Genome-wide association (GWA) studies offer the opportunity to identify genes that contribute to naturally occurring variation in quantitative traits. However, GWA relies exclusively on statistical association, so functional validation is necessary to make strong claims about gene function. We used a combination of gene-disruption platforms (Tnt1 retrotransposons, hairpin RNA-interference constructs, and CRISPR/Cas9 nucleases) together with randomized, well-replicated experiments to evaluate the function of genes that an earlier GWA study in Medicago truncatula had identified as candidates contributing to variation in the symbiosis between legumes and rhizobia. We evaluated ten candidate genes found in six clusters of strongly associated single nucleotide polymorphisms, selected on the basis of their strength of statistical association, proximity to annotated gene models, and root or nodule expression. We found statistically significant effects on nodule production for three candidate genes, each validated in two independent mutants. Annotated functions of these three genes suggest their contributions to quantitative variation in nodule production occur through processes not previously connected to nodulation, including phosphorous supply and salicylic acid-related defense response. These results demonstrate the utility of GWA combined with reverse mutagenesis technologies to discover and validate genes contributing to naturally occurring variation in quantitative traits. The results highlight the potential for GWA to complement forward genetics in identifying the genetic basis of ecologically and economically important traits.

Genetic Basis of Chronotype in Humans: Insights From Three Landmark GWAS

Study Objectives

Chronotype, or diurnal preference, refers to behavioral manifestations of the endogenous circadian system that governs preferred timing of sleep and wake. As variations in circadian timing and system perturbations are linked to disease development, the fundamental biology of chronotype has received attention for its role in the regulation and dysregulation of sleep and related illnesses. Family studies indicate that chronotype is a heritable trait, thus directing attention toward its genetic basis. Although discoveries from molecular studies of candidate genes have shed light onto its genetic architecture, the contribution of genetic variation to chronotype has remained unclear with few related variants identified. In the advent of large-scale genome-wide association studies (GWAS), scientists now have the ability to discover novel common genetic variants associated with complex phenotypes. Three recent large-scale GWASs of chronotype were conducted on subjects of European ancestry from the 23andMe cohort and the UK Biobank. This review discusses the findings of these landmark GWASs in the context of prior research.

Methods

We systematically reviewed and compared methodological and analytical approaches and results across the three GWASs of chronotype.

Results

A good deal of consistency was observed across studies with 9 genes identified in 2 of the 3 GWASs. Several genes previously unknown to influence chronotype were identified.

Conclusions

GWAS is an important tool in identifying common variants associated with the complex chronotype phenotype, the findings of which can supplement and guide molecular science. Future directions in model systems and discovery of rare variants are discussed.

GWAS Identifies New Loci for Painful Temporomandibular Disorder: Hispanic Community Health Study/Study of Latinos

Temporomandibular disorder (TMD) is a musculoskeletal condition characterized by pain and reduced function in the temporomandibular joint and/or associated masticatory musculature. Prevalence in the United States is 5% and twice as high among women as men. We conducted a discovery genome-wide association study (GWAS) of TMD in 10,153 participants (769 cases, 9,384 controls) of the US Hispanic Community Health Study/Study of Latinos (HCHS/SOL). The most promising single-nucleotide polymorphisms (SNPs) were tested in meta-analysis of 4 independent cohorts. One replication cohort was from the United States, and the others were from Germany, Finland, and Brazil, totaling 1,911 TMD cases and 6,903 controls. A locus near the sarcoglycan alpha ( SGCA), rs4794106, was suggestive in the discovery analysis ( P = 2.6 × 10⁶) and replicated (i.e., 1-tailed P = 0.016) in the Brazilian cohort. In the discovery cohort, sex-stratified analysis identified 2 additional genome-wide significant loci in females. One lying upstream of the relaxin/insulin-like family peptide receptor 2 ( RXP2) (chromosome 13, rs60249166, odds ratio [OR] = 0.65, P = 3.6 × 10^-8) was replicated among females in the meta-analysis (1-tailed P = 0.052). The other (chromosome 17, rs1531554, OR = 0.68, P = 2.9 × 10^-8) was replicated among females (1-tailed P = 0.002), as well as replicated in meta-analysis of both sexes (1-tailed P = 0.021). A novel locus at genome-wide level of significance (rs73460075, OR = 0.56, P = 3.8 × 10^-8) in the intron of the dystrophin gene DMD (X chromosome), and a suggestive locus on chromosome 7 (rs73271865, P = 2.9 × 10^-7) upstream of the Sp4 Transcription Factor ( SP4) gene were identified in the discovery cohort, but neither of these was replicated. The SGCA gene encodes SGCA, which is involved in the cellular structure of muscle fibers and, along with DMD, forms part of the dystrophin-glycoprotein complex. Functional annotation suggested that several of these variants reside in loci that regulate processes relevant to TMD pathobiologic processes.