Results Of Genome-wide Association Studies Research Articles

Migration Rates on Swim Plates Vary between Escherichia coli Soil Isolates: Differences Are Associated with Variants in Metabolic Genes.

This study investigates migration phenotypes of 265 Escherichia coli soil isolates from the Buffalo River basin in Minnesota, USA. Migration rates on semisolid tryptone swim plates ranged from nonmotile to 190% of the migration rate of a highly motile E. coli K-12 strain. The nonmotile isolate, LGE0550, had mutations in flagellar and chemotaxis genes, including two IS3 elements in the flagellin-encoding gene fliC. A genome-wide association study (GWAS), associating the migration rates with genetic variants in specific genes, yielded two metabolic variants (rygD-serA and metR-metE) with previous implications in chemotaxis. As a novel way of confirming GWAS results, we used minimal medium swim plates to confirm the associations. Other variants in metabolic genes and genes that are associated with biofilm were positively or negatively associated with migration rates. A determination of growth phenotypes on Biolog EcoPlates yielded differential growth for the 10 tested isolates on d-malic acid, putrescine, and d-xylose, all of which are important in the soil environment. IMPORTANCE E. coli is a Gram-negative, facultative anaerobic bacterium whose life cycle includes extra host environments in addition to human, animal, and plant hosts. The bacterium has the genomic capability of being motile. In this context, the significance of this study is severalfold: (i) the great diversity of migration phenotypes that we observed within our isolate collection supports previous (G. NandaKafle, A. A. Christie, S. Vilain, and V. S. Brözel, Front Microbiol 9:762, 2018, https://doi.org/10.3389/fmicb.2018.00762; Y. Somorin, F. Abram, F. Brennan, and C. O'Byrne, Appl Environ Microbiol 82:4628-4640, 2016, https://doi.org/10.1128/AEM.01175-16) ideas of soil promoting phenotypic heterogeneity, (ii) such heterogeneity may facilitate bacterial growth in the many different soil niches, and (iii) such heterogeneity may enable the bacteria to interact with human, animal, and plant hosts.

An adaptive test based on principal components for detecting multiple phenotype associations using GWAS summary data.

Extensive evidence from genome-wide association studies (GWAS) has shown that jointly analyzing multiple phenotypes can improve the power of the association test compared to the traditional single variant versus single trait approach. Here we propose an adaptive test based on principal components (ATPC) that is powerful and efficient for discovering the association between a single variant and multiple traits. Our method only needs GWAS summary statistics that are often available. We first estimate the trait correlation matrix by LD score regression. Then, based on the correlation matrix, we construct a series of test statistics that contain different numbers of principal components. The ultimate test statistic combines the P values of these principal component-based statistics by using the aggregated Cauchy association test. The analytical P-value of the test statistic can be computed quickly without the permutation process, which is the notable feature of our proposed method. The extensive simulation studies demonstrate that ATPC can control the type I error rates and have powerful and robust performance compared to several existing tests in a wide range of simulation settings. The analysis of the lipids GWAS summary data from the Global Lipids Genetics Consortium shows that ATPC identifies 230 new SNPs that are missed by the original single trait association analysis. By searching the GWAS Catalog, some SNPs and mapped genes identified by ATPC are reported to be associated with lipid traits. Through further analysis for GWAS results, we also find some Gene Ontology terms and biological pathways related to lipids.

Examining the shared etiology of psychopathology with genome-wide association studies.

Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.

Robustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression.

Genetic association signals have been mostly found in noncoding regions through genome-wide association studies (GWAS), suggesting the roles of gene expression regulation in human diseases and traits. However, there has been limited success in colocalizing expression quantitative trait locus (eQTL) with disease-associated variants. Mediated expression score regression (MESC) is a recently proposed method to quantify the proportion of trait heritability mediated by genetically regulated gene expressions (GReX). Applications of MESC to GWAS results have yielded low estimation of mediated heritability for many traits. As MESC relies on stringent independence assumptions between cis-eQTL effects, gene effects, and nonmediated SNP effects, it may fail to characterize the true relationships between those effect sizes, which leads to biased results. Here, we consider the robustness of MESC to investigate whether the low fraction of mediated heritability inferred by MESC reflects biological reality for complex traits or is an underestimation caused by model misspecifications. Our results suggest that MESC may lead to biased estimates of mediated heritability with misspecification of gene annotations leading to underestimation, whereas misspecification of SNP annotations may lead to overestimation. Furthermore, errors in eQTL effect estimates may lead to underestimation of mediated heritability.

All Staphylococcus aureus bacteraemia-inducing strains can cause infective endocarditis: Results of GWAS and experimental animal studies

We aimed at determining whether specific S. aureus strains cause infective endocarditis (IE) in the course of Staphylococcus aureus bacteraemia (SAB). A genome-wide association study (GWAS) including 924 S. aureus genomes from IE (274) and non-IE (650) SAB patients from international cohorts was conducted, and a subset of strains was tested with two experimental animal models of IE, one investigating the early step of bacterial adhesion to inflamed mice valves, the second evaluating the local and systemic developmental process of IE on mechanically-damaged rabbit valves. The genetic profile of S. aureus IE and non-IE SAB strains did not differ when considering single nucleotide polymorphisms, coding sequences, and k-mers analysed in GWAS. In the murine inflammation-induced IE model, no difference was observed between IE and non-IE SAB strains both in terms of adhesion to the cardiac valves and in the propensity to cause IE; in the mechanical IE-induced rabbit model, there was no difference between IE and non-IE SAB strains regarding the vegetation size and CFU. All strains of S. aureus isolated from SAB patients must be considered as capable of causing this common and lethal infection once they have accessed the bloodstream.

Genome-wide association mapping highlights candidate genes and immune genotypes for net blotch and powdery mildew resistance in barley

Net blotch (NB) and powdery mildew (PM) are major barley diseases with the potential to cause a dramatic loss in grain yield. Breeding for resistant barley genotypes in combination with identifying candidate resistant genes will accelerate the genetic improvement for resistance to NB and PM. To address this challenge, a set of 122 highly diverse barley genotypes from 34 countries were evaluated for NB and PM resistance under natural infection for in two growing seasons. Moreover, four yield traits; plant height (Ph), spike length (SL), spike weight (SW), and the number of spikelets per spike (NOS) were recorded. High genetic variation was found among genotypes in all traits scored in this study. No significant phenotypic correlation was found in the resistance between PM and NB. Immune genotypes for NB and PM were identified. A total of 21 genotypes were immune to both diseases. Of the 21 genotypes, the German genotype HOR_9570 was selected as the most promising genotype that can be used for future breeding programs. Furthermore, a genome-wide association study (GWAS) was used to identify resistant alleles to PM and NB. The results of GWAS revealed a set of 14 and 25 significant SNPs that were associated with increased resistance to PM and NB, respectively. This study provided very important genetic resources that are highly resistant to the Egyptian PM and NB pathotypes and revealed SNP markers that can be utilized to genetically improve resistance to PM and NB.

Genome-wide association study reveals a genomic region on SSC7 simultaneously associated with backfat thickness, skin thickness and carcass length in a Large White × Tongcheng advanced generation intercross resource population.

In order to identify important genetic markers associated with backfat thickness, skin thickness and carcass length, we first constructed Large White × Tongcheng (Chinese local breed), an advanced generation intercross population, then performed a genome-wide association study (GWAS) to reveal the key genomic region associated with these traits through whole genome sequencing. The GWAS results of backfat thickness, skin thickness and carcass length showed that all the most significant SNPs associated with these three traits were located on SSC7, and that 14.9, 27.0 and 21.1% of phenotypic variances were explained by these three SNPs, respectively. Through linkage disequilibrium analysis, we found that a 66.9 kb (30.23-30.31Mb) genetic region was overlapped among these three traits, and that NUDT3 and HMGA1 were identified as major candidate genes for backfat thickness and carcass length, and GRM4 as a potential candidate gene for skin thickness. In addition, 13 highly linked SNPs significantly associated with the three traits were also identified in overlapped region, and three completely linked SNPs formed two haplotypes Q and q. The backfat thickness of individuals with the qq genotype was significantly lower than that of individuals with the QQ genotype, but their carcass length and skin thickness were significantly higher than those with the QQ genotype. Our detected candidate genes and SNPs will provide the foundation for genetic improvement of these three traits.

Identification of new resistance loci against wheat sharp eyespot through genome-wide association study.

Wheat sharp eyespot caused by Rhizoctonia cerealis is a serious pathogenic disease affecting plants. The effective strategy for controlling this disease is breeding resistant cultivar. However, to date, no wheat varieties are fully resistant to sharp eyespot, and only a few quantitative trait loci (QTLs) have been shown to be associated with sharp eyespot resistance. To understand the genetic basis of this disease, a genome-wide association study (GWAS) of sharp eyespot resistance in 262 varieties from all China wheat regions was conducted. After cultivation for three years, only 6.5% of the varieties were resistant to sharp eyespot. Notably, the varieties from the middle and lower Yangtze River displayed higher sharp eyespot resistance than those from Huanghuai wheat zone. Only two varieties had the same resistance level to the control Shanhongmai. The results of GWAS showed that 5 single nucleotide polymorphism (SNP) loci were markedly related to sharp eyespot resistance in the three years repeatedly, and two QTLs, qSE-6A and qSE-7B, on chromosome 6A and 7B were identified. Based on the 'CG' haplotypes of significant SNPs, we found that the two QTLs exhibited additive effects on attenuating sharp eyespot resistance. These results provide novel insights into the genetic basis of sharp eyespot resistance in China wheat varieties. The SNPs related to sharp eyespot resistance can be applied for marker-assisted selection in plant breeding.

Lipase‐a single‐nucleotide polymorphism rs143793106 is associated with increased risk of aggressive periodontitis by negative influence on the cytodifferentiation of human periodontal ligament cells

Aggressive periodontitis (AgP) is characterized by general health and rapid destruction of periodontal tissue. The familial aggregation of this disease highlights the involvement of genetic factors in its pathogeny. We conducted a genome-wide association study (GWAS) to identify AgP-related genes in a Japanese population, and the lipid metabolism-related gene, lipase-a, lysosomal acid type (LIPA), was suggested as an AgP candidate gene. However, there is no report about the expression and function(s) of LIPA in periodontal tissue. Hence, we studied the involvement of how LIPA and its single-nucleotide polymorphism (SNP) rs143793106 in AgP by functional analyses of LIPA and its SNP in human periodontal ligament (HPDL) cells. GWAS was performed using the genome database of Japanese AgP patients, and the GWAS result was confirmed using Sanger sequencing. We examined the mRNA expression level of LIPA and the protein expression level of the encoded protein lysosomal acid lipase (LAL) in periodontium-composing cells using conventional and real-time polymerase chain reaction (PCR) and western blotting, respectively. Lentiviral vectors expressing LIPA wild-type (LIPA WT) and LIPA SNP rs143793106 (LIPA mut) were transfected into HPDL cells. Western blotting was performed to confirm the transfection. LAL activity of transfected HPDL cells was determined using the lysosomal acid lipase activity assay. Transfected HPDL cells were cultured in mineralization medium. During the cytodifferentiation of transfected HPDL cells, mRNA expression of calcification-related genes, alkaline phosphatase (ALPase) activity and calcified nodule formation were assessed using real-time PCR, ALPase assay, and alizarin red staining, respectively. The GWAS study identified 11 AgP-related candidate genes, including LIPA SNP rs143793106. The minor allele frequency of LIPA SNP rs143793106 in AgP patients was higher than that in healthy subjects. LIPA mRNA and LAL protein were expressed in HPDL cells; furthermore, they upregulated the cytodifferentiation of HPDL cells. LAL activity was lower in LIPA SNP-transfected HPDL cells during cytodifferentiation than that in LIPA WT-transfected HPDL cells. In addition, ALPase activity, calcified nodule formation, and calcification-related gene expression levels were lower during cytodifferentiation in LIPA SNP-transfected HPDL cells than those in LIPA WT-transfected HPDL cells. LIPA, identified as an AgP-related gene in a Japanese population, is expressed in HPDL cells and is involved in regulating cytodifferentiation of HPDL cells. LIPA SNP rs143793106 suppressed cytodifferentiation of HPDL cells by decreasing LAL activity, thereby contributing to the development of AgP.

Genetic basis of the early heading of high-latitude weedy rice

Japonica rice (Oryza sativa L.) is an important staple food in high-latitude regions and is widely distributed in northern China, Japan, Korea, and Europe. However, the genetic diversity of japonica rice is relatively narrow and poorly adapted. Weedy rice (Oryza sativa f. spontanea) is a semi-domesticated rice. Its headings are earlier than the accompanied japonica rice, making it a potential new genetic resource, which can make up for the defects of wild rice that are difficult to be directly applied to japonica rice improvement caused by reproductive isolation. In this study, we applied a natural population consisting of weedy rice, japonica landrace, and japonica cultivar to conduct a genome-wide association study (GWAS) of the heading date and found four loci that could explain the natural variation of the heading date in this population. At the same time, we developed recombinant inbred lines (RILs) crossed by the early-heading weedy rice WR04-6 and its accompanied japonica cultivar ShenNong 265 (SN265) to carry out a QTL mapping analysis of the heading date and mapped four quantitative trait locus (QTLs) and three epistatic effect gene pairs. The major locus on chromosome 6 overlapped with the GWAS result. Further analysis found that two genes, Hd1 and OsCCT22, on chromosome 6 (Locus 2 and Locus 3) may be the key points of the early-heading character of weedy rice. As minor effect genes, Dth7 and Hd16 also have genetic contributions to the early heading of weedy rice. In the process of developing the RIL population, we introduced fragments of Locus 2 and Locus 3 from the weedy rice into super-high-yielding japonica rice, which successfully promoted its heading date by at least 10 days and expanded the rice suitable cultivation area northward by about 400km. This study successfully revealed the genetic basis of the early heading of weedy rice and provided a new idea for the genetic improvement of cultivated rice by weedy rice.

A Million Veteran Program GWAS of Alzheimer’s Disease and Related Dementias in African Americans Identifies Multiple Genome‐Wide Significant Dementia Risk Loci

AbstractBackgroundWhile genome wide association studies (GWASs) of Alzheimer’s Disease (AD) in European ancestry cohorts (EUR) have identified >70 potentially independent AD risk loci, progress in non‐European populations has lagged. In this study, data from US Veterans of African ancestry (AFR) from the Million Veteran Program (MVP) biorepository were used to identify genetic factors associated with AD and related dementias (ADRD).MethodUsing the VA electronic medical record, 4,012 AFR ADRD cases (algorithm includes codes for AD and dementias such as vascular dementia) and 18,435 dementia‐free AFR controls were identified for inclusion in the GWAS. A GWAS was also performed using proxy dementia based on survey‐reported AFR participant parental history of AD or other dementia that included 4,385 maternal cases, 2,256 paternal cases, and 45,970 controls. Meta‐analysis of the case control and proxy results for was performed and then subsequently combined with results from a AFR AD GWAS conducted by the Alzheimer Disease Genetics Consortium (ADGC; Kunkle et al., 2021).ResultThe AFR MVP GWAS (case‐control + proxy) yielded genome‐wide significant associations with several loci including APOE (p=2.48x10‐101), ROBO1 (rs11919682, p=1.63x10‐8), and RP11‐340A13.2 (rs148433063, p=8.56x10‐9. The ROBO1 and RP11‐240A13.2 SNPs were not replicated in the ADGC sample (missing or not significant). The meta‐analysis of MVP and ADGC GWAS results (Table 1) additionally identified genome significant SNPs near known AD risk genes TREM2 (rs73427293, p=2.95x10‐9), CD2AP (rs7738720, p=1.14x10‐9), and ABCA7 (rs73505251, p=3.26x10‐10). Comparison of expression of genes near variants with suggestive evidence of association (p<5x10‐7) in the brains of EUR AD cases and controls from Framingham Heart Study, Religious Orders Study/Rush Memory and Aging Project, Mayo‐Mount Sinai Brain Bank, and Boston University Brain Bank (Panitch et al.) identified several differentially expressed genes including EML6.ConclusionThe AFR dementia GWAS presented here is the largest to date. It increased the number of genome wide significant common‐variant dementia loci reported in AFR cohorts from two to six, including genes previously implicated in EUR cohorts. Increasing representation of AFRs is an important priority in genetic studies and may lead to increased insight into AD pathophysiology and reduce health disparities.

GWAS in tetraploid potato: identification and validation of SNP markers associated with glycoalkaloid content.

The online version contains supplementary material available at 10.1007/s11032-022-01344-2.

Localization of the quantitative trait loci related to lodging resistance in spring bread wheat (Triticum aestivum L.).

The yield and grain quality of spring and winter wheat signif icantly depends on varieties' resistance to lodging, the genetic basis of this trait being quantitative and controlled by a large number of loci. Therefore, the study of the genetic architecture of the trait becomes necessary for the creation and improvement of modern wheat varieties. Here we present the results of localization of the genomic regions associated with resistance to lodging, plant height, and upper internode diameter in Russian bread wheat varieties. Phenotypic screening of 97 spring varieties and breeding lines was carried out in the f ield conditions of the West Siberian region during 2017-2019. It was found that 54 % of the varieties could be characterized as medium and highly resistant to lodging. At the same time, it was noted that the trait varied over the years. Twelve varieties showed a low level of resistance in all years of evaluation. Plant height-based grouping of the varieties showed that 19 samples belonged to semi-dwarfs (60-84 cm), and the rest were included in the group of standard-height plants (85-100 cm). Quantitative trait loci (QTL) mapping was performed by means of genome-wide association study (GWAS) using 9285 SNP markers. For lodging resistance, plant height, and upper internode diameter, 26 signif icant associations (-log p > 3) were found in chromosomes 1B, 2A, 3A, 3D, 4A, 5A, 5B, 5D, 6A, and 7B. The results obtained suggest that the regions of 700-711 and 597-618 Mb in chromosomes 3A and 6A, respectively, may contain clusters of genes that affect lodging resistance and plant height. No chromosome regions colocalized with the QTLs as sociated with lodging resistance or upper internode diameter were found. The present GWAS results may be important for the development of approaches for creating lodging-resistant varieties through marker-assisted and genomic selection.

CRISPR/Cas9 genome editing demonstrates functionality of the autoimmunity-associated SNP rs12946510

Genome-wide association studies (GWAS) map genetic associations of complex traits with precision limited to a linkage disequilibrium group. To translate GWAS results into new understanding of disease mechanisms, individual causative polymorphisms and their target genes should be identified. CRISPR/Cas9 genome editing can be used to create isogenic cell lines bearing alternative genotypes of candidate single-nucleotide polymorphisms to test their causality and to reveal gene targets. An intergenic polymorphism rs12946510 is associated with multiple sclerosis, inflammatory bowel disease and asthma. We created sublines of the T-helper cell line bearing alternative genotypes of rs12946510 and showed that its risk (“T”) allele is associated with lower expression of IKZF3 and ORMDL3 genes and reduced cell activation. Our editing procedure can become an effective tool for discovering new genes involved in pathogenesis of complex diseases.

A Genome-Wide Association Study (GWAS) of Event-Free Survival (EFS) in Follicular Lymphoma Patients Treated with Front-Line Immunochemotherapy: A Lysa, Iowa/Mayo MER, and FIL Study

Background: Few studies have evaluated the role of host (germline) genetics in predicting outcome in follicular lymphoma (FL) patients. Using patients treated with rituximab (R) based immunochemotherapy (IC) from 3 clinical trials and one prospective observational study, we conducted the first genome-wide association study (GWAS) of prognosis in FL patients to identify germline genetic predictors of event-free survival (EFS) overall as well as failure within the first 24 months after treatment initiation (EFS24). Methods: We conducted a GWAS study of FL patients (n=1,054) treated in first-line therapy with R-CHOP (n=726, 69%), R-CVP (n=255, 24%) and R-FM (fludarabine and mitoxantrone) (n=73, 7%) from the following studies: PRIMA (n=391) and RELEVANCE (n=205) of the Lymphoma Study Association; FOL05 (n=199) of the Fondazione Italiana Linfomi; and the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER) (n=259). After IC, 437 patients (41%) received R-maintenance. Genotyping was performed using Human Core exome (PRIMA, RELEVANCE, FOL05) and 660 Quad (MER) BeadChips. Minimac4/1000G was used to impute additional SNPs. After stringent quality control measures, 1,287,537 SNPs across the 4 cohorts with a minor allele frequency (MAF) >0.05 were evaluated. Association testing was conducted assuming a log-additive genetic model. We calculated the hazard ratios (HR) by Cox regression analysis for EFS. Results were adjusted for FLIPI score, sex, cohort, principal component analysis of population stratification, treatment (R-CHOP/R-FM vs. R-CVP), and use of R-maintenance (modeled as a time-dependent variable). To identify early clinical failures, we conducted a GWAS using a piecewise Cox model to find SNPs associated with events within the first 24 months (EFS24) vs after 24 months. Because of the heterogeneity of our prognostic cohorts, we utilized a cross-validation statistical technique to identify robust findings that replicate across cohorts. The data were iteratively analyzed in discovery and validation blocks using a "leave-one-cohort-out" (LOCO) strategy: in each round, one cohort was left for validation while the other three cohorts were combined for discovery. Top SNPs were selected from each discovery block of three cohorts with an inclusive p<0.0001 threshold to move to validation in the remaining cohort. SNPs were considered validated with a p<0.1 threshold and a consistent HR direction between discovery and validation blocks. Validated SNPs were then combined into a final pooled analysis and were ranked based on p-value and number of cross validations in the context of standard pooled GWAS results. Results: In the final analysis for EFS prediction, the top SNP was rs72625024 at 3q27.3 (MAF=0.11; HR=0.62, p=9.37x10-8), which was discovered and validated in all 4 LOCO rounds. Figure 1 shows this and other top SNPs from the LOCO analysis mapped onto traditional pooled GWAS results. This SNP also predicted overall survival (OS) in a model independent of FLIPI and other prognostic factors (HR=0.69, p=0.013). rs72625024 is near FETUB (fetuin B), which is involved in the inactivation of the PI3K/AKT signaling pathway. The other top SNPs for EFS were at 3q21.1 and 8p23.2, but they did not reach statistical significance and showed weak validation in the LOCO design. In the analysis of EFS24, rs114695031 at 14q32.13 predicted events during the first 24 months and was discovered and validated in all 4 LOCO rounds (MAF=0.20; HR=0.58, p=1.93x10-8) (Figure 2). This variant is an intronic SNP localized in T Cell Leukemia/Lymphoma 6 gene, a long non-coding RNA and putative tumor suppressor. Suggestive associations for early failure were observed for rs12824955 at 12q24.11 (MAF=0.27; HR=0.60, p=1.46x10-7) and validated in 3 of 4 LOCO rounds, while rs333302 at 3q21.1 (MAF=0.42; HR=1.61, p=1.15x10-6) did not reach statistical significance. For events after 24 months, no SNPs were statistically significant. Conclusions: In this large GWAS study, a locus at 3q27.3 (near FETUB) was associated with EFS after adjustment for other prognostic factors and treatment. Furthermore, a genome-wide significant locus (p<5x10-8) at 14q32.13 (near TCL6) predicted EFS24, suggesting a specific role in early failures. These results, requiring additional external validation, support a role for inherited susceptibility impacting outcomes in IC-treated FL and that may vary by timing of failures. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Novel Genetic Associations for Skin Aging Phenotypes and Validation of Previously Reported Skin GWAS Results

Facial skin characteristics are complex traits determined by genetic and environmental factors. Because genetic factors continuously influenced facial skin characteristics, identifying associations between genetic variants [single-nucleotide polymorphisms (SNPs)] and facial skin characteristics may clarify genetic contributions. We previously reported a genome-wide association study (GWAS) for five skin phenotypes (wrinkles, pigmentation, moisture content, oil content, and sensitivity) conducted in 1079 subjects. In this study, face measurements and genomic data were generated for 261 samples, and significant SNPs described in previous papers were verified. We conducted a GWAS to identify additional genetic markers using the combined population of the previous study and current study samples. We identified 6 novel significant loci and 21 suggestive loci in the combined study with p-values &lt; 5.0 × 10−8 (wrinkles: 4 SNPs; moisture content: 148 SNPs; pigmentation: 6 SNPs; sensitivity: 18 SNPs). Identifying SNPs using molecular genetic functional analysis is considered necessary for studying the mechanisms through which these genes affect the skin. We confirmed that of 23 previously identified SNPs, none were replicated. SNPs that could not be verified in a combined study may have been accidentally identified in an existing GWAS, or the samples added to this study may not have been a sufficient sample number to confirm those SNPs. The results of this study require validation in other independent population groups or larger samples. Although this study requires further research, it has the potential to contribute to the development of cosmetic-related genetic research in the future.

Quality Control Procedures for Genome-Wide Association Studies.

Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of many complex diseases. Regardless of the context, the practical utility of this information ultimately depends upon the quality of the data used for statistical analyses. Quality control (QC) procedures for GWAS are constantly evolving. Here, we enumerate some of the challenges in QC of genotyped GWAS data and describe the approaches involving genotype imputation of a sample dataset along with post-imputation quality assurance, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of the GWAS data (genotyped and imputed), including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We provide detailed guidelines along with a sample dataset to suggest current best practices and discuss areas of ongoing and future research. © 2022 Wiley Periodicals LLC.

Comparative Analysis of Multiple GWAS Results Identifies Metabolic Pathways Associated with Resistance to A. flavus Infection and Aflatoxin Accumulation in Maize.

Aflatoxins are carcinogenic secondary metabolites produced by several species of Aspergillus, including Aspergillus flavus, an important ear rot pathogen in maize. Most commercial corn hybrids are susceptible to infection by A. flavus, and aflatoxin contaminated grain causes economic damage to farmers. The creation of inbred lines resistant to Aspergillus fungal infection or the accumulation of aflatoxins would be aided by knowing the pertinent alleles and metabolites associated with resistance in corn lines. Multiple Quantitative Trait Loci (QTL) and association mapping studies have uncovered several dozen potential genes, but each with a small effect on resistance. Metabolic pathway analysis, using the Pathway Association Study Tool (PAST), was performed on aflatoxin accumulation resistance using data from four Genome-wide Association Studies (GWAS). The present research compares the outputs of these pathway analyses and seeks common metabolic mechanisms underlying each. Genes, pathways, metabolites, and mechanisms highlighted here can contribute to improving phenotypic selection of resistant lines via measurement of more specific and highly heritable resistance-related traits and genetic gain via marker assisted or genomic selection with multiple SNPs linked to resistance-related pathways.

177 GENOME-WIDE ASSOCIATION ANALYSIS OF THE FRAILTY PHENOTYPE IN UK BIOBANK HIGHLIGHTS CARDIOMETABOLIC AND AUTOIMMUNE SIGNATURES IN AGEING

Abstract Background Frailty is a state of advanced biological age that is characterized by multisystem physiological decline and advanced risk to adverse health outcomes. One approach to defining frailty is using the Fried frailty phenotype, a five-point list of health-related criteria used to score individuals as non-frail, pre-frail, or frail. The biological basis of frailty is not fully understood, nor why some experience frailty at younger ages. Between 30%-45% of frailty risk is estimated to be genetic. This study aimed to investigate the genetic basis of frailty phenotype risk using data from UK Biobank. Methods UK Biobank is a large-scale biomedical database of community dwelling adults (n = 502,529, age range: 37-73 years, 54% female). UK Biobank has genome-wide genotyping (approx. 93 million variants), health, and demographic data for all participants. A genome-wide association study (GWAS) of the frailty phenotype was performed on British and Irish adults aged 60 to 70 years (n = 157,720) to identify heritable factors which predict frailty progression in later life. Functional mapping was performed to determine genes and biological pathways enriched in GWAS results. Results 95 single nucleotide polymorphisms (SNPs) from three independent genomic risk loci were significantly associated (p &amp;lt; 5e-8) with the frailty phenotype in UK Biobank participants. Three genes, PPP1R3A, LONRF2, and AIF1 were statistically enriched with genetic variants. Tissue-specific expression analysis indicated genes differentially expressed in blood vessels were enriched. Linkage Disequilibrium Score Regression (lambda = 1.2005, intercept = 1.0006) indicated GWAS test statistic inflation resulting from polygenicity. SNP-based heritability was estimated to be 6.34% (SE: 0.36%). Conclusion SNP-based heritability of the frailty phenotype was lower than expected in comparison to previous reports of 30%-45%. Statistically significant genomic risk loci, genes, and tissue-enrichment pointed towards dysregulation of cardiometabolic, cardiovascular, and immunological processes in frailty risk, contrasting to brain pathways enriched in previous genomic analyses of the frailty index.

Polygenic power calculator: Statistical power and polygenic prediction accuracy of genome-wide association studies of complex traits.

Power calculation is a necessary step when planning genome-wide association studies (GWAS) to ensure meaningful findings. Statistical power of GWAS depends on the genetic architecture of phenotype, sample size, and study design. While several computer programs have been developed to perform power calculation for single SNP association testing, it might be more appropriate for GWAS power calculation to address the probability of detecting any number of associated SNPs. In this paper, we derive the statistical power distribution across causal SNPs under the assumption of a point-normal effect size distribution. We demonstrate how key outcome indices of GWAS are related to the genetic architecture (heritability and polygenicity) of the phenotype through the power distribution. We also provide a fast, flexible and interactive power calculation tool which generates predictions for key GWAS outcomes including the number of independent significant SNPs, the phenotypic variance explained by these SNPs, and the predictive accuracy of resulting polygenic scores. These results could also be used to explore the future behaviour of GWAS as sample sizes increase further. Moreover, we present results from simulation studies to validate our derivation and evaluate the agreement between our predictions and reported GWAS results.