Future Genome-wide Association Studies Research Articles

GWAS advancements to investigate disease associations and biological mechanisms.

Genome-wide association studies (GWAS) have been instrumental in elucidating the genetic architecture of various traits and diseases. Despite the success of GWAS, inherent limitations such as identifying rare and ultra-rare variants, the potential for spurious associations, and in pinpointing causative agents can undermine diagnostic capabilities. This review provides an overview of GWAS and highlights recent advances in genetics that employ a range of methodologies, including Whole Genome Sequencing (WGS), Mendelian Randomization (MR), the Pangenome's high-quality T2T-CHM13 panel, and the Human BioMolecular Atlas Program (HuBMAP), as potential enablers of current and future GWAS research. State of the literature demonstrate the capabilities of these techniques in enhancing the statistical power of GWAS. WGS, with its comprehensive approach, captures the entire genome, surpassing the capabilities of the traditional GWAS technique focused on predefined Single Nucleotide Polymorphism (SNP) sites. The Pangenome's T2T-CHM13 panel, with its holistic approach, aids in the analysis of regions with high sequence identity, such as segmental duplications (SDs). Mendelian Randomization has advanced causative inference, improving clinical diagnostics and facilitating definitive conclusions. Furthermore, spatial biology techniques like HuBMAP, enable 3D molecular mapping of tissues at single-cell resolution, offering insights into pathology of complex traits. This study aims to elucidate and advocate for the increased application of these technologies, highlighting their potential to shape the future of GWAS research.

Genome wide association studies for carcass traits measured by video image analysis in crossbred lambs

This is the first UK genome wide association study investigating potential links between Video Image Analysis (VIA) carcass traits and molecular polymorphisms in crossbred sheep. Phenotypic and genotypic data were collected from two crossbred lamb populations: Texel x Scotch Mule (TxSM, n = 2330) and Texel x Lleyn (TxL, n = 3816). Traits measured included live weights at birth, eight weeks and weaning (∼15 weeks). VIA-predicted traits included total weights and weights of fat, muscle and bone in the whole carcass and primal (hind leg, saddle, shoulder) regions. Within-breed heritabilities estimated for the VIA traits ranged from 0.01 to 0.70, indicating potential for inclusion of some traits in breeding programmes. The two crossbred populations differed in SNPs associated with different traits. Two SNPs on chromosomes two (s74618.1) and eight (s68536.1), respectively, reached genome-wise significance for TxSM, explaining <1% of trait variance, for whole carcass fat and muscle weights, hind leg and saddle fat weights and shoulder bone weights. For TxL, four SNPs reached genome-wise significance, on chromosome two for hind leg muscle weight (OAR2_117,959,202 and OAR2_11804335), on chromosome 10 for whole carcass bone weight (OAR19_8,995,957.1), and on chromosome 19 for weaning weight (s40847.1), each explaining <1% of trait genetic variation. Differences in apparent genetic control of carcass traits may be influenced by the lambs' cross-breed, but also by management decisions affecting environmental variance and trait definitions, which should be understood in order to define protocols for incorporation of carcass traits into (cross)breeding programmes. ImplicationsCombining VIA-measured carcass traits with conventional production traits in a breeding programme could potentially improve the production and product quality of meat sheep. Phenotypes for VIA traits could be collected relatively easily if VIA machines were present at all abattoir sites. The current study and future Genome Wide Association Studies may help to identify potentially informative molecular markers, that explain large proportions of the genetic variance observed in VIA-measured carcass traits. Including this information in the estimation of breeding values could increase the accuracy of prediction, increasing the potential rate of genetic improvement for product quality. This study confirms the polygenic architecture of the investigated carcass traits, with a small number of molecular markers that each explain a small amount of genetic variation. Further studies across breed types are recommended to further test and validate molecular markers for traits related to lamb carcass quality, as measured by video image analysis.

Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores.

Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.

Text mining of electronic health records can validate a register-based diagnosis of epilepsy and subgroup into focal and generalized epilepsy.

Combining population-based health registries and electronic health records offers the opportunity to create large, phenotypically detailed patient cohorts of high quality. In this study, we used text mining of clinical notes to confirm International Classification of Diseases, 10th Revision (ICD-10)-registered epilepsy diagnoses and classify patients according to focal and generalized epilepsy types. Using the Danish National Patient Registry, we identified patients who between 2006 and 2016 received an ICD-10 diagnosis of epilepsy. To validate the epilepsy diagnosis and stratify patients into focal and generalized epilepsy types, we constructed dictionaries for text mining-based extraction of clinical notes. Two physicians manually reviewed the clinical notes for a total of 527 patients and assigned epilepsy diagnoses, which were compared with the text-mined diagnoses. We identified 23 632 patients with an ICD-10 diagnosis of epilepsy, of whom 50% were registered with an unspecified epilepsy diagnosis. In total, 11 211 patients were considered likely to have epilepsy by text mining, with an F1 measure ranging from 82% to 90%. Manual review of the electronic health records for 310 patients revealed a false discovery rate of 29%. This rate was decreased to 4% by the text mining algorithm. The weighted average F1 measure for text mining-assigned epilepsy types was 79% (82% for focal and 76% for generalized epilepsy). Text mining successfully assigned a focal or generalized epilepsy type to 92% of the text mining-eligible patients registered with unspecified epilepsy. Text mining of electronic health records can be used to establish a patient cohort with much higher likelihood of having a diagnosis of epilepsy and a focal or generalized epilepsy type compared to the cohort created from ICD-10 epilepsy codes alone. We believe the concept will be essential for future genome-wide and phenome-wide association studies and subsequently the development of precision medicine for epilepsy patients.

The current state and future of cardiometabolic polygenic risk scores in European and non-European population cohorts

Abstract Funding Acknowledgements Type of funding sources: None. Background A polygenic risk score (PRS) is derived from a genome-wide association study (GWAS) and represents an aggregate of thousands of single-nucleotide polymorphisms (SNPs) that provide a baseline estimate of an individual’s genetic risk for a specific disease or trait at birth. Cardiometabolic disease represents a set of disease processes that historically have disproportionally affected underrepresented racial and minority groups. Furthermore, these groups represent a population generally not well captured by traditional risk scores compared to European cohorts. Since the first GWAS studying myocardial infarction was published, PRSs have increasingly been seen as a promising tool to improve risk stratification of non-European populations. However, how PRSs can be best used in clinical practice remains unclear. Purpose To provide an overview of the PRSs related to cardiometabolic disease, analyze the ancestral diversity of GWAS cohorts, and discuss the evidence supporting their clinical applications. Methods The Preferred Reporting Items For Systematic Reviews and Meta-analysis extension for Scoping Reviews protocol was used to conduct a scoping review of the MEDLINE, EMBASE, and CENTRAL databases. English studies that published a PRS related to atrial fibrillation (AF), cerebrovascular disease (CVD), coronary artery disease (CAD), dyslipidemia, heart failure, heritable cardiomyopathy, hypertension, and type 2 diabetes were reviewed. Results Across the 4,863 studies screened, 82 articles met the inclusion criteria. The most common PRS related to CAD, followed by hypertension and CVD. Limited ancestral diversity was observed as most studies (56) included only individuals of European ancestry. A smaller proportion of studies (16) published PRSs derived in multi-ancestry cohorts. Only ten studies published a PRS derived solely from a sample population of non-European ancestry (Chinese, East Asian, Japanese, and Korean). The predictive performance of most PRSs was similar to or superior to traditional risk factors. More than half of the included studies (42) reported an integrated risk model combining a PRS with traditional risk factors or a clinical risk tool (FRS, PCE, CHADS2). The integrated risk model consistently improved predictive accuracy, but few studies investigated the performance in a non-European population. Conclusion In conclusion, this scoping review is the first of its kind and reports strong evidence for the clinical use of PRSs in AF, CAD, CVD, and hypertension. However, most PRSs are derived in cohorts of European ancestry, which contributes to a lack of PRS transferability across different ancestral groups, likely exacerbating health inequities. Future prospective studies should focus on further establishing the clinical utility of PRSs. Additionally, diversity in future GWAS cohorts is essential to ensure that PRSs reflect the multi-ancestry society at large.

Structural variation among assembled genomes facilitates development of rapid and low-cost NOR-linked markers and NOR-telomere junction mapping in Arabidopsis.

Genome-wide structural variants we identified and new NOR-linked markers we developed would be useful for future genome-wide association studies (GWAS), and for new gene/trait mapping purposes. Bioinformatic alignment of the assembled genomes of Col-0 and Sha ecotypes of Arabidopsis thaliana revealed ~ 13,000 genome-wide structural variants involving simple insertions or deletions and repeat contractions or expansions. Using some of these structural variants, we developed new, rapid, and low-cost PCR-based molecular markers that are genetically linked to the nucleolus organizer regions (NORs). A. thaliana has two NORs, one each on chromosome 2 (NOR2) and chromosome 4 (NOR4). Both NORs are ~ 4Mb each, and hundreds of 45S ribosomal RNA (rRNA) genes are tandemly arrayed at these loci. Using previously characterized recombinant inbred lines (RILs) derived from Sha xCol-0 crosses, we validated the utility of the newly developed NOR-linked markers in genetically mapping rRNA genes and the associated telomeres to either NOR2 or NOR4. Lastly, we sequenced Sha genome using Oxford Nanopore Technology (ONT) and used the data to obtain sequences of NOR-telomere junctions, and with the help of RILs, we mapped them as new genetic markers to their respective NORs (NOR2-TEL2N and NOR4-TEL4N). The structural variants obtained from this study would serve as valuable data for genome-wide association studies (GWAS), and to rapidly design more genome-wide genetic (molecular) markers for new gene/trait mapping purposes.

An exponential increase in QTL detection with an increased sample size.

Power analyses are often used to determine the number of animals required for a genome-wide association study (GWAS). These analyses are typically intended to estimate the sample size needed for at least 1 locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real data set that consisted of 3,173 male and female adult N/NIH heterogeneous stock rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in subsamples of the full data set. The subsampling analysis was conducted for 4 traits with low (0.15 ± 0.03), medium (0.31 ± 0.03 and 0.36 ± 0.03), and high (0.46 ± 0.03) SNP-based heritabilities. For each trait, we subsampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

Abstract P339: The Clinical Application and Ancestral Diversity of Cardiometabolic Polygenic Risk Scores

Introduction: A polygenic risk score (PRS) is derived from a genome-wide association study (GWAS) and represents an aggregate of thousands of single-nucleotide polymorphisms (SNPs) that provide a baseline estimate of an individual’s genetic risk for a specific disease or trait at birth. Cardiometabolic disease represents a set of disease processes that historically have disproportionally affected underrepresented racial and minority groups. Furthermore, these groups represent a population generally not well captured by traditional risk scores compared to European cohorts. Since the first GWAS studying myocardial infarction was published, PRSs have increasingly been seen as a promising tool to improve risk stratification of non-European populations. However, how PRSs can be best used in clinical practice remains unclear. Hypothesis: We provide an overview of the PRSs related to cardiometabolic disease, analyze the ancestral diversity of GWAS cohorts, and discuss the evidence supporting their clinical applications. Methods: The Preferred Reporting Items For Systematic Reviews and Meta-analysis extension for Scoping Reviews protocol was used to conduct a scoping review of the MEDLINE, EMBASE, and CENTRAL databases. English studies that published a PRS related to atrial fibrillation (AF), cerebrovascular disease (CVD), coronary artery disease (CAD), dyslipidemia, heart failure, heritable cardiomyopathy, hypertension, and type 2 diabetes were reviewed. Results: Across the 4,863 studies screened, 82 articles met the inclusion criteria. The most common PRS related to CAD, followed by hypertension and CVD. Limited ancestral diversity was observed as most studies (56) included only individuals of European ancestry. A smaller proportion of studies (16) published PRSs derived in multi-ancestry cohorts. Only ten studies published a PRS derived solely from a sample population of non-European ancestry (Chinese, East Asian, Japanese, and Korean). The predictive performance of most PRSs was similar to or superior to traditional risk factors. More than half of the included studies (42) reported an integrated risk model combining a PRS with traditional risk factors or a clinical risk tool (FRS, PCE, CHADS2). The integrated risk model consistently improved predictive accuracy, but few studies investigated the performance in a non-European population. Conclusion: In conclusion, this scoping review reports strong evidence for the clinical use of PRSs in AF, CAD, CVD, and hypertension. However, most PRSs are derived in cohorts of European ancestry, which contributes to a lack of PRS transferability across different ancestral groups, likely exacerbating health inequities. Future prospective studies should focus on further establishing the clinical utility of PRSs. Additionally, diversity in future GWAS cohorts is essential to ensure that PRSs reflect the multi-ancestry society at large.

Behavioral and Physiological Reactions to a Sudden Novel Object in the Weanling Horse: Quantitative Phenotypes for Future GWAS

The startle response can be defined as a reflexive reaction to the sudden appearance of a novel stimulus that influences the survival and resilience of animals. In domesticated species, the behavioral component of the startle response can, in some cases, cause serious injury to the animal or human handlers if inappropriately expressed. Here, we describe a longitudinal study in a population of stock-type horses that quantified behavioral startle responses elicited by the presentation of a sudden novel object (rapidly opening umbrella). The study was performed in weanling foals across four consecutive years (n = 74, mean age = 256 days). Behavioral assays for the startle response phenotype focused on six behavioral variables: latency to return to the feed pan (seconds), maximum distance fled (meters), proportion of time spent walking or trotting (seconds), and how long a horse spent standing facing away from or toward the novel object. We observed behavioral startle response variables in relation to cardiac response, age, and sex for each individual. Each horse's cardiac startle response pattern was determined and categorized into heart rate response cluster groups identified as accelerators and decelerators. Using principal component analysis (PCA) with a factor rotation, we identified "startle response" phenotypes that summarize the behavioral and physiological variables. The largest component of variation, Factor 1, comprised 32.5% of the behavioral variable with a positive correlation with latency and distance, and was not influenced by sex or age. Factor 2 comprised 23.2% of the variation, and was positively correlated with activity level performed such as proportion of time spent walking and/or trotting. Horses with the accelerator type cardiac response had significantly higher Factor 1 scores than decelerators but did not differ in Factor 2. Future work includes expanding our sample size to conduct a genome-wide association study (GWAS) to identify novel genetic loci influencing behavioral startle reactions using recorded behavioral and physiological phenotypes.

Genetics of nonpharmacological treatments of depression.

Nonpharmacological antidepressant treatments are effective and well tolerated in selected patients. However, response is heterogeneous and validated biomarkers would be precious to aid treatment choice. We searched Pubmed, Scopus, and Google Scholar until May 2022 for original articles evaluating the association of genetic variables with the efficacy of nonpharmacological treatments for major depressive episodes. Most studies analyzed small sample sizes using the candidate gene approach, leading to poorly replicated findings that need to be interpreted cautiously. The few available methylome-wide and genome-wide association studies (GWASs) considered only electroconvulsive therapy (ECT) and cognitive-behavioral therapy in small samples, providing interesting findings by using polygenic risk scores. A deeper knowledge of the genetic factors implicated in treatment response may lead to a better understanding of the neurobiological mechanisms of nonpharmacological therapies for depression, and depression itself. Future GWAS are going to expand their sample size, thanks to consortia such as the gen-ECT-ic consortium.

Intramembranous bone regeneration in diversity outbred mice is heritable.

There are over one million cases of failed bone repair in the U.S. annually, resulting in substantial patient morbidity and societal costs. Multiple candidate genes affecting bone traits such as bone mineral density have been identified in human subjects and animal models using genome-wide association studies (GWAS). This approach for understanding the genetic factors affecting bone repair is impractical in human subjects but could be performed in a model organism if there is sufficient variability and heritability in the bone regeneration response. Diversity Outbred (DO) mice, which have significant genetic diversity and have been used to examine multiple intact bone traits, would be an excellent possibility. Thus, we sought to evaluate the phenotypic distribution of bone regeneration, sex effects and heritability of intramembranous bone regeneration on day 7 following femoral marrow ablation in 47 12-week old DO mice (23 males, 24 females). Compared to a previous study using 4 inbred mouse strains, we found similar levels of variability in the amount of regenerated bone (coefficient of variation of 86% v. 88%) with approximately the same degree of heritability (0.42 v. 0.49). There was a trend toward more bone regeneration in males than females. The amount of regenerated bone was either weakly or not correlated with bone mass at intact sites, suggesting that the genetic factors responsible for bone regeneration and intact bone phenotypes are at least partially independent. In conclusion, we demonstrate that DO mice exhibit variation and heritability of intramembranous bone regeneration that will be suitable for future GWAS.

Systematic review of genome-wide association studies of anxiety disorders and neuroticism

Objectives To summarise SNP associations identified by genome-wide association studies (GWASs) of anxiety disorders and neuroticism; to appraise the quality of individual studies, and to assess the ancestral diversity of study participants. Methods We searched PubMed, Scopus, PsychInfo and PubPsych for GWASs of anxiety disorders, non-diagnostic traits (such as anxiety sensitivity), and neuroticism, and extracted all SNPs that surpassed genome-wide significance. We graded study quality using Q-genie scores and reviewed the ancestral diversity of included participants. Results 32 studies met our inclusion criteria. A total of 563 independent significant variants were identified, of which 29 were replicated nominally in independent samples, and 3 were replicated significantly. The studies had good global quality, but many smaller studies were underpowered. Phenotypic heterogeneity for anxiety (and less so for neuroticism) seemed to reflect the complexity of capturing this trait. Ancestral diversity was poor, with 70% of studies including only populations of European ancestry. Conclusion The functionality of genes identified by GWASs of anxiety and neuroticism deserves further investigation. Future GWASs should have larger sample sizes, more rigorous phenotyping and include more ancestrally diverse population groups.

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms.

To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI= 0.84-2.48%, neffective= 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI= 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg|= 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Contemporary GWAS studies of depression: the critical role of phenotyping

The need to use large samples to identify the genetic risk loci of mental disorders has led us to the dilemma of phenotyping quality. Especially this problem relates to such common mental disorders as depression (lifetime prevalence 16.2%). On the one hand, there is a very resource-intensive method of capturing patient data by physicians using diagnostic criteria of mental disorders (DSM-V/ICD-10). On the other, there is a popular method of minimal phenotyping using hospital registers, self-reports of respondents on symptoms, diagnosis and treatment of depression. To date, there is no ideal method for phenotyping depression because all of them focus only on its clinical symptoms. The active usage of minimal phenotyping in Genome-Wide Association Study (GWAS) has led to a significant increase in both clinical and genetic heterogeneity of depression. However, an important limitation of using DSM-V/ICD-10 is the high cost of phenotyping due to the involvement of medical specialists. Thus, the most rational is to use electronic diagnostic questionnaires based on DSM-V/ICD-10 criteria. Such an approach will accelerate the increase in research capacity, but will preserve all internal contradictions inherent in official diagnostic classifications (heterogeneity of phenotypes, absence of objective diagnostic criteria, categorical approach, etc.). In this regard, the critical role of psychiatric epidemiology is growing both in the development of standardized tools for operationalized diagnostic criteria and in future GWAS by introducing new phenotypic subtypes of depression and its dimensions.

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator.

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

Polygenic risk score for general cognitive function is associated with measures of cognition in South Asians from the LASI-DAD Study.

Genome wide association studies (GWAS) conducted primarily in European Ancestry (EA) have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with general cognitive function. The association between these SNPs and cognitive function has not yet been evaluated in South Asians yet, either individually or in polygenic risk scores (PRS) which aggregate the effects from many SNPs across the genome. The goal of this study was to investigate whether SNPs identified in EA GWAS, either individually or as a PRS, were associated with a general cognitive factor and the Hindi version of the Mini-Mental State Examination (HMSE) score in 932 South Asians from the Diagnostic Assessment of Dementia for the Longitudinal Aging Study of India (LASI-DAD). Participants were genotyped using the Illumina Global Screening Array and imputed to 1000G Phase 3v5. We used linear models to assess the association between 130 top SNPs from the EA GWAS (p<5e-08) and both measures of cognitive function after controlling for age, gender, and population structure. We also evaluated the association between PRSs using the top GWAS SNPs and the cognitive measures using the same models. Finally, we estimated the variation in cognitive function explained by the cognitive function PRS, Alzheimer's disease (AD) PRSs, and/or APOE e2 and e4 genotypes individually or simultaneously. Preliminary analyses showed that none of the GWAS SNPs were significantly associated either of the cognitive measures after multiple testing correction. The PRS, however, was significantly associated with the general cognitive factor and HMSE score (p<0.025). The PRS explained 0.40% and 0.59% of the variance in the general cognitive factor and HMSE score, and explained 1.50% and 1.85% of the variance when coupled with AD PRSs and APOE genotypes. SNPs identified for cognitive function in EA GWAS may not be as strongly associated in South Asians. However, the genetic risk score for both general cognitive function and AD contribute additively to cognitive function in LASI-DAD participants. Future large scale GWAS of general cognitive function and AD are needed to identify specific risk variants for cognition in South Asians.

A genome-wide association analysis for body weight at 35\xa0days measured on 137,343 broiler chickens

BackgroundBody weight (BW) is an economically important trait in the broiler (meat-type chickens) industry. Under the assumption of polygenicity, a “large” number of genes with “small” effects is expected to control BW. To detect such effects, a large sample size is required in genome-wide association studies (GWAS). Our objective was to conduct a GWAS for BW measured at 35 days of age with a large sample size.MethodsThe GWAS included 137,343 broilers spanning 15 pedigree generations and 392,295 imputed single nucleotide polymorphisms (SNPs). A false discovery rate of 1% was adopted to account for multiple testing when declaring significant SNPs. A Bayesian ridge regression model was implemented, using AlphaBayes, to estimate the contribution to the total genetic variance of each region harbouring significant SNPs (1 Mb up/downstream) and the combined regions harbouring non-significant SNPs.ResultsGWAS revealed 25 genomic regions harbouring 96 significant SNPs on 13 Gallus gallus autosomes (GGA1 to 4, 8, 10 to 15, 19 and 27), with the strongest associations on GGA4 at 65.67–66.31 Mb (Galgal4 assembly). The association of these regions points to several strong candidate genes including: (i) growth factors (GGA1, 4, 8, 13 and 14); (ii) leptin receptor overlapping transcript (LEPROT)/leptin receptor (LEPR) locus (GGA8), and the STAT3/STAT5B locus (GGA27), in connection with the JAK/STAT signalling pathway; (iii) T-box gene (TBX3/TBX5) on GGA15 and CHST11 (GGA1), which are both related to heart/skeleton development); and (iv) PLAG1 (GGA2). Combined together, these 25 genomic regions explained ~ 30% of the total genetic variance. The region harbouring significant SNPs that explained the largest portion of the total genetic variance (4.37%) was on GGA4 (~ 65.67–66.31 Mb).ConclusionsTo the best of our knowledge, this is the largest GWAS that has been conducted for BW in chicken to date. In spite of the identified regions, which showed a strong association with BW, the high proportion of genetic variance attributed to regions harbouring non-significant SNPs supports the hypothesis that the genetic architecture of BW35 is polygenic and complex. Our results also suggest that a large sample size will be required for future GWAS of BW35.

The genetic structure of the Turkish population reveals high levels of variation and admixture

The construction of population-based variomes has contributed substantially to our understanding of the genetic basis of human inherited disease. Here, we investigated the genetic structure of Turkey from 3,362 unrelated subjects whose whole exomes (n = 2,589) or whole genomes (n = 773) were sequenced to generate a Turkish (TR) Variome that should serve to facilitate disease gene discovery in Turkey. Consistent with the history of present-day Turkey as a crossroads between Europe and Asia, we found extensive admixture between Balkan, Caucasus, Middle Eastern, and European populations with a closer genetic relationship of the TR population to Europeans than hitherto appreciated. We determined that 50% of TR individuals had high inbreeding coefficients (≥0.0156) with runs of homozygosity longer than 4 Mb being found exclusively in the TR population when compared to 1000 Genomes Project populations. We also found that 28% of exome and 49% of genome variants in the very rare range (allele frequency < 0.005) are unique to the modern TR population. We annotated these variants based on their functional consequences to establish a TR Variome containing alleles of potential medical relevance, a repository of homozygous loss-of-function variants and a TR reference panel for genotype imputation using high-quality haplotypes, to facilitate genome-wide association studies. In addition to providing information on the genetic structure of the modern TR population, these data provide an invaluable resource for future studies to identify variants that are associated with specific phenotypes as well as establishing the phenotypic consequences of mutations in specific genes.

An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population.

Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F2 population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.

X-chromosome influences on neuroanatomical variation in humans.

The X-chromosome has long been hypothesized to have a disproportionate influence on the brain based on its enrichment for genes that are expressed in the brain and associated with intellectual disability. Here, we verify this hypothesis through partitioned heritability analysis of X-chromosome influences (XIs) on human brain anatomy in 32,256 individuals from the UK Biobank. We first establish evidence for dosage compensation in XIs on brain anatomy-reflecting larger XIs in males compared to females, which correlate with regional sex-biases in neuroanatomical variance. XIs are significantly larger than would be predicted from X-chromosome size for the relative surface area of cortical systems supporting attention, decision-making and motor control. Follow-up association analyses implicate X-linked genes with pleiotropic effects on cognition. Our study reveals a privileged role for the X-chromosome in human neurodevelopment and urges greater inclusion of this chromosome in future genome-wide association studies.