Genome-wide association study of body height in African Americans: the Women's Health Initiative SNP Health Association Resource (SHARe)

Application of Predictive Analytics in Pregnancy, Birth, and Postpartum Nursing Care

ABSTRACT

Predictive analytics has emerged as a promising approach for improving reproductive health care and patient outcomes. During pregnancy and birth, the ability to accurately predict risks and complications could enable earlier interventions and reduce adverse events. However, there are challenges and ethical considerations for implementing predictive models in perinatal care settings. We introduce major concepts in predictive analytics and describe application of predictive modeling to perinatal care topics such as fertility, preeclampsia, labor onset, vaginal birth after cesarean, uterine rupture, induction outcomes, postpartum hemorrhage, and postpartum mood disorders. Although some predictive models have achieved adequate accuracy (AUC 0.7-0.9), most require additional external validation across diverse populations and practice settings. Bias, particularly racial bias, remains a key limitation of current models. Nurses and advanced practice nurses, including nurse practitioners certified registered nurse anesthetists, and nurse-midwives, play a vital role in ensuring high-quality data collection and communicating predictive model outputs to clinicians and users of the health care system. Addressing the ethical challenges and limitations of predictive analytics is imperative to equitably translate these tools to support patient-centered perinatal care.

General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals

Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.g. genotypes and gene expression levels) on a phenotype, particularly while accommodating routine issues, such as having related subjects' data in analyses. In this paper, we extend an existing composite kernel machine regression model to integrate two multi-omics data types, while accommodating for general correlation structures amongst outcomes. Due to the kernel machine regression framework, our methods allow for the integration of high-dimensional omics data with small, nonlinear, and interactive effects, and accommodation of general study designs. Here, we focus on scientific questions that aim to assess the association between a functional grouping (such as a gene or a pathway) and a quantitative trait of interest. We use a kernel machine regression to integrate the two multi-omics data types, as they may relate to the trait, and perform a global test of association. We demonstrate the advantage of this approach over single data type association tests via simulation. Finally, we apply this method to a large, multi-ethnic data set to investigate how predicted gene expression and rare genetic variation may be related to two platelet traits.

Environmental adaptation and genetic insights: Cloning, bioinformatics, and tissue expression analysis of the LCORL gene in Guangxi Partridge Chicken

To investigate the structure of the ligand-dependent nuclear receptor corepressor-like (LCORL) gene-encoded protein and its gene expression in tissues, the Guangxi partridge chicken was utilized as experimental material for cloning the LCORL gene, followed by bioinformatics and tissue expression profile analyses. The results revealed that the coding region of the LCORL gene was 1557 bp, comprising 518 amino acids. Sequence comparison with the reference sequence (entry number: NM_001031160.3) indicated the presence of three non-synonymous mutations and one synonymous mutation. Interspecies homology analysis demonstrated that the relationship between the LCORL gene of the Guangxi partridge chicken and Chicken (Gallus gallus) was the highest, which was 99.7%. Examination of the phylogenetic tree indicated that a clear genetic gap in the LCORL gene between birds and between birds and mammals. The isoelectric point (pI) of the LCORL protein was 8.55, categorizing it as a basic protein. Hydrophilic analysis revealed an average hydrophilic acid sequence of -0.712, indicating that it is a hydrophilic protein. The results of functional domain prediction demonstrated that the protein contains only the HTH domain and does not belong to transmembrane or secreted proteins. The LCORL protein is classified as an irregularly folded protein without ligands. Quantitative reverse transcription PCR (QRT-PCR) revealed that the expression of the LCORL gene was most prominent in the testis, suggesting a connection to the development and growth of rooster testis tissue, thus influencing its growth. These findings provide a theoretical basis for further research on the biological function of the chicken LCORL gene. This study not only advances our understanding of the role of LCORL gene in environmental adaptive function, but also supports its potential application in poultry genetic improvement and sustainable farming.

Adjusting for principal components can induce collider bias in genome-wide association studies

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken

In local chickens targeted for niche markets, genotyping costs are relatively high due to the small population size and diverse breeding goals. The single-step genomic best linear unbiased prediction (ssGBLUP) model, which combines pedigree and genomic information, has been introduced to increase the accuracy of genomic estimated breeding value (GEBV). Therefore, this model may be more beneficial than the genomic BLUP (GBLUP) model for genomic selection in local chickens. Additionally, the single-step genome-wide association study (ssGWAS) can be used to extend the ssGBLUP model results to animals with available phenotypic information but without genotypic data. In this study, we compared the accuracy of (G)EBVs using the pedigree-based BLUP (PBLUP), GBLUP, and ssGBLUP models. Moreover, we conducted single-SNP GWAS (SNP-GWAS), GBLUP-GWAS, and ssGWAS methods to identify genes associated with egg production traits in the NCHU-G101 chicken to understand the feasibility of using genomic selection in a small population. The average prediction accuracy of (G)EBV for egg production traits using the PBLUP, GBLUP, and ssGBLUP models is 0.536, 0.531, and 0.555, respectively. In total, 22 suggestive- and 5% Bonferroni genome-wide significant-level SNPs for total egg number (EN), average laying rate (LR), average clutch length, and total clutch number are detected using 3 GWAS methods. These SNPs are mapped onto Gallus gallus chromosomes (GGA) 4, 6, 10, 18, and 25 in NCHU-G101 chicken. Furthermore, through SNP-GWAS and ssGWAS methods, we identify 2 genes on GGA4 associated with EN and LR: ENSGALG00000023172 and PPARGC1A. In conclusion, the ssGBLUP model demonstrates superior prediction accuracy, performing on average 3.41% than the PBLUP model. The implications of our gene results may guide future selection strategies for Taiwan Country chickens. Our results highlight the applicability of the ssGBLUP model for egg production traits selection in a small population, specifically NCHU-G101 chicken in Taiwan.

Identification of a novel QTL for lean meat percentage using imputed genotypes

Lean meat percentage is a critical production trait in pig breeding systems with direct implications for the sustainability of the industry. In this study, we conducted a genome-wide association study for lean meat percentage using a cohort of 850 Duroc × (Landrace × Yorkshire) crossbred pigs and we identified QTL on SSC3 and SSC18. Based on the predicted effect of imputed variants and using the PigGTEx database of molecular QTL, we prioritized candidate genes and SNPs located within the QTL regions, which may be involved in the regulation of porcine leanness. Our results indicate that a nonsense mutation in ZC3HAV1L on SSC18 has a direct effect on lean meat percentage.

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Unlocking the Transcriptional Control of NCAPG in Bovine Myoblasts: CREB1 and MYOD1 as Key Players

Muscle formation directly determines meat production and quality. The non-SMC condensin I complex subunit G (NCAPG) is strongly linked to the growth features of domestic animals because it is essential in controlling muscle growth and development. This study aims to elucidate the tissue expression level of the bovine NCAPG gene, and determine the key transcription factors for regulating the bovine NCAPG gene. In this study, we observed that the bovine NCAPG gene exhibited high expression levels in longissimus dorsi and spleen tissues. Subsequently, we cloned and characterized the promoter region of the bovine NCAPG gene, consisting of a 2039 bp sequence, through constructing the deletion fragment double-luciferase reporter vector and site-directed mutation-identifying core promoter region with its key transcription factor binding site. In addition, the key transcription factors of the core promoter sequence of the bovine NCAPG gene were analyzed and predicted using online software. Furthermore, by integrating overexpression experiments and the electrophoretic mobility shift assay (EMSA), we have shown that cAMP response element binding protein 1 (CREB1) and myogenic differentiation 1 (MYOD1) bind to the core promoter region (-598/+87), activating transcription activity in the bovine NCAPG gene. In conclusion, these findings shed important light on the regulatory network mechanism that underlies the expression of the NCAPG gene throughout the development of the muscles in beef cattle.

Comparative population genomics analysis uncovers genomic footprints and genes influencing body weight trait in Chinese indigenous chicken

Body weight of chicken is a typical quantitative trait, which shows phenotypic variations due to selective breeding. Despite some QTL loci have been obtained, the body weight of native chicken breeds in different geographic regions varies greatly, its genetic basis remains unresolved questions. To address this issue, we analyzed 117 Chinese indigenous chickens from 10 breeds (Huiyang Bearded, Xinhua, Hotan Black, Baicheng You, Liyang, Yunyang Da, Jining Bairi, Lindian, Beijing You, Tibetan). We applied fixation index (FST) analysis to find selected genomic regions and genes associated with body weight traits. Our study suggests that NELL1, XYLT1, and NCAPG/LCORL genes are strongly selected in the body weight trait of Chinese indigenous chicken breeds. In addition, the IL1RAPL1 gene was strongly selected in large body weight chickens, while the PCDH17 and CADM2 genes were strongly selected in small body weight chickens. This result suggests that the patterns of genetic variation of native chicken and commercial chicken, and/or distinct local chicken breeds may follow different evolutionary mechanisms.

Strategies for the Genomic Analysis of Admixed Populations

Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.

Accurate modeling of replication rates in genome-wide association studies by accounting for Winner's Curse and study-specific heterogeneity

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex human traits, but only a fraction of variants identified in discovery studies achieve significance in replication studies. Replication in genome-wide association studies has been well-studied in the context of Winner's Curse, which is the inflation of effect size estimates for significant variants due to statistical chance. However, Winner's Curse is often not sufficient to explain lack of replication. Another reason why studies fail to replicate is that there are fundamental differences between the discovery and replication studies. A confounding factor can create the appearance of a significant finding while actually being an artifact that will not replicate in future studies. We propose a statistical framework that utilizes genome-wide association studies and replication studies to jointly model Winner's Curse and study-specific heterogeneity due to confounding factors. We apply this framework to 100 genome-wide association studies from the Human Genome-Wide Association Studies Catalog and observe that there is a large range in the level of estimated confounding. We demonstrate how this framework can be used to distinguish when studies fail to replicate due to statistical noise and when they fail due to confounding.

GATA binding protein 5-mediated transcriptional activation of transmembrane protein 100 suppresses cell proliferation, migration and epithelial-to-mesenchymal transition in prostate cancer DU145 cells

It has been reported that transmembrane protein 100 (TMEM100) acts as a tumor regulator in several types of cancers. However, whether the expression of TMEM100 is associated with the development and prognosis of prostate cancer (PCa) remains elusive. Therefore, the present study aimed to uncover the role of GATA binding protein 5 (GATA5)-mediated activation of TMEM100 in the proliferation, migration and epithelial-to-mesenchymal transition (EMT) of PCa cells. The expressions of TMEM100 and GATA5 in PCa patients were analyzed by the GEPIA database. The binding site of GATA5 and TMEM100 promoter was predicted by the JASPAR database. Expressions of TMEM100 and GATA5 in PCa cells were detected by qRT-PCR and Western blot analysis. Cell Counting Kit 8 and colony formation assays were performed to measure cell proliferation. In addition, cell migration, invasion and the expression of EMT-associated proteins were evaluated using wound healing, transwell assay and Western blotting assays, respectively. The bioinformatics analysis revealed that TMEM100 was downregulated in PCa and was associated with overall survival of PCa. In addition, TMEM10 overexpression attenuated cell proliferation, migration, invasion and EMT in PCa cells. The interaction between TMEM100 and GATA5 was verified using dual luciferase reporter and chromatin immunoprecipitation assays. Furthermore, the results showed that GATA5 was downregulated and GATA5 silencing reversed the inhibitory effects of TMEM10 on PCa cells. Overall, the current study suggested that the GATA5-mediated transcriptional activation of TMEM100 could affect the behavior of PCa cells and was associated with poor prognosis in PCa.

Single Nucleotide Polymorphism of TWIST2 May Be a Modifier for the Association between High-Density Lipoprotein Cholesterol and Blood Lead (Pb) Level

The association between lead (Pb) exposure and lower high-density lipoprotein cholesterol (HDL-C) was reported; however, the mechanism was unclear. Our purpose was to investigate the association of Pb, lipid profile, and to study the associated SNPs using a genome-wide association study (GWAS). A total of 511 participants were recruited to check blood Pb levels, lipid profile, and genotypes with Taiwan Biobank version 2.0 (TWB2). Our main result shows that HDL-C was significantly negatively associated with blood Pb levels, adjusted for gender, body mass index (BMI), and potential confounders. In addition, via the TWB2 GWAS, only two SNPs were found, including rs150813626 (single-nucleotide variation in the TWIST2 gene on chromosome 2), and rs1983079 (unclear SNP on chromosome 3). Compared to the rs150813626 GG carriers, the AA and AG carriers were significantly and negatively associated with HDL-C. We analyzed the interaction of rs150813626 SNP and blood Pb, and the HDL-C was consistently and negatively associated with blood Pb, male, BMI, and the rs150813626 AA and AG carriers. Moreover, the rs150813626 AA and blood Pb interaction was significantly and positively associated with HDL-C. In conclusion, the SNPs rs150813626 and rs1983079 were significantly associated with HDL-C in Pb-exposed workers. Furthermore, the interaction of rs150813626 AA and blood Pb had a positive influence on HDL-C. TWIST may inhibit osteoblast maturation, which might relate to bone Pb deposition and calcium metabolism. The mechanism needs more investigation in the future.

Role of Sex on the Genetic Susceptibility to Childhood Asthma in Latinos and African Americans

Asthma is a respiratory disease whose prevalence changes throughout the lifespan and differs by sex, being more prevalent in males during childhood and in females after puberty. In this study, we assessed the influence of sex on the genetic susceptibility to childhood asthma in admixed populations. Sex-interaction and sex-stratified genome-wide association studies (GWAS) were performed in 4291 Latinos and 1730 African Americans separately, and results were meta-analyzed. Genome-wide (p ≤ 9.35 × 10-8) and suggestive (p ≤ 1.87 × 10-6) population-specific significance thresholds were calculated based on 1000 Genomes Project data. Additionally, protein quantitative trait locus (pQTL) information was gathered for the suggestively associated variants, and enrichment analyses of the proteins identified were carried out. Four independent loci showed interaction with sex at a suggestive level. The stratified GWAS highlighted the 17q12-21 asthma locus as a contributor to asthma susceptibility in both sexes but reached genome-wide significance only in females (p-females < 9.2 × 10-8; p-males < 1.25 × 10-2). Conversely, genetic variants upstream of ligand-dependent nuclear receptor corepressor-like gene (LCORL), previously involved in height determination and spermatogenesis, were associated with asthma only in males (minimum p = 5.31 × 10-8 for rs4593128). Enrichment analyses revealed an overrepresentation of processes related to the immune system and highlighted differences between sexes. In conclusion, we identified sex-specific polymorphisms that could contribute to the differences in the prevalence of childhood asthma between males and females.

Detection of whole genome selection signatures of Pakistani Teddy goat

BACKGROUND

Natural and artificial selection tend to cause variability that contributes to shape the genome of livestock in a way that differentiates them among the animal kingdom. The particular aim here is to identify positive selection signatures with whole genome pooled-sequence data of Pakistani Teddy goat.

METHODS AND RESULTS

Paired-end alignment of 635,357,043 reads of Teddy goat with (ARS1) reference genome assembly was carried out. Pooled-Heterozygosity (Hp) and Tajima's D (TD) are applied for validation and getting better hits of selection signals, while pairwise F_ST statistics is conducted on Teddy vs. Bezoar (wild goat ancestor) for genomic differentiation, moreover annotation of regions under positive selection was also performed. Hp score with - ZHp > 5 detected six windows having highest hits on Chr. 29, 9, 25, 15 and 14 that harbor HRASLS5, LACE1 and AXIN1 genes which are candidate for embryonic development, lactation and body height. Secondly, - ZTD value of > 3.3 showed 4 windows with very strong hits on Chr.5 & 9 which harbor STIM1 and ADM genes related to body mass and weight. Lastly, - ZF_ST < - 5 generated four strong signals on Chr.5 & 12 harbor LOC102183233 gene. Other significant selection signatures encompass genes associated with wool production, prolificacy and coat colors traits in this breed.

CONCLUSIONS

In brief, this study identified the genes under selection in Pakistani Teddy goat that will be helpful to refining the marker-assisted breeding policies and converging required production traits within and across other goat breeds and to explore full genetic potential of this valued species of livestock.

Genomic analyses reveal distinct genetic architectures and selective pressures in Chinese donkeys

Donkey (Equus asinus) is an important livestock animal in China because of its draft and medicinal value. After a long period of natural and artificial selection, the variety and phenotype of donkeys have become abundant. We clarified the genetic and demographic characteristics of Chinese domestic donkeys and the selection pressures by analyzing 78 whole genomes from 12 breeds. According to population structure, most Chinese domestic donkeys showed a dominant ancestral type. However, the Chinese donkeys still represented a significant geographical distribution trend. In the selective sweep, gene annotation, functional enrichment, and differential expression analyses between large and small donkey groups, we identified selective signals, including NCAPG and LCORL, which are related to rapid growth and large body size. Our findings elucidate the evolutionary history and formation of different donkey breeds and provide theoretical insights into the genetic mechanism underlying breed characteristics and molecular breeding programs of donkey clades.

Single nucleotide polymorphisms affect miRNA target prediction in bovine

Single nucleotide polymorphisms (SNPs) can have significant effects on phenotypic characteristics in cattle. MicroRNAs (miRNAs) are small, non-coding RNAs that act as post-transcriptional regulators by binding them to target mRNAs. In the present study, we scanned ~56 million SNPs against 1,064 bovine miRNA sequences and analyzed, in silico, their possible effects on target binding prediction, primary miRNA formation, association with QTL regions and the evolutionary conservation for each SNP locus. Following target prediction, we show that 71.6% of miRNA predicted targets were altered as a consequence of SNPs located within the seed region of the mature miRNAs. Next, we identified variations in the Minimum Free Energy (MFE), which represents the capacity to alter molecule stability and, consequently, miRNA maturation. A total of 48.6% of the sequences analyzed showed values within those previously reported as sufficient to alter miRNA maturation. We have also found 131 SNPs in 46 miRNAs, with altered target prediction, occurring in QTL regions. Lastly, analysis of evolutionary conservation scores for each SNP locus suggested that they have a conserved biological function through the evolutionary process. Our results suggest that SNPs in microRNAs have the potential to affect bovine phenotypes and could be of great value for genetic improvement studies, as well as production.

TMEM100 expression suppresses metastasis and enhances sensitivity to chemotherapy in gastric cancer

The gene encoding transmembrane protein 100 (TMEM100) was first discovered to be transcribed by the murine genome. It has been recently proven that TMEM100 contributes to hepatocellular carcinoma and non-small-cell lung carcinoma (NSCLC). This study investigates the impact of TMEM100 expression on gastric cancer (GC). TMEM100 expression was remarkably downregulated in GC samples compared to the surrounding non-malignant tissues (p < 0.01). Excessive TMEM100 expression prohibited the migration and invasion of GC cells without influencing their growth. However, TMEM100 knockdown restored their migration and invasion potential. Additionally, TMEM100 expression restored the sensitivity of GC cells to chemotherapeutic drugs such as 5-fluouracil (5-FU) and cisplatin. In terms of TMEM100 modulation, it was revealed that BMP9 rather than BMP10, is the upstream modulator of TM3M100. HIF1α downregulation modulated the impact of TMEM100 on cell migration, chemotherapy sensitivity and invasion in GC cells. Eventually, the in vivo examination of TMEM100 activity revealed that its upregulation prohibits the pulmonary metastasis of GC cells and increases the sensitivity of xenograft tumors to 5-FU treatment. In conclusion, TMEM100 serves as a tumor suppressor in GC and could be used as a promising target for the treatment of GC and as a predictor of GC clinical outcome.

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

The distribution of runs of homozygosity in the genome of river and swamp buffaloes reveals a history of adaptation, migration and crossbred events

Background

Water buffalo is one of the most important livestock species in the world. Two types of water buffalo exist: river buffalo (Bubalus bubalis bubalis) and swamp buffalo (Bubalus bubalis carabanensis). The buffalo genome has been recently sequenced, and thus a new 90 K single nucleotide polymorphism (SNP) bead chip has been developed. In this study, we investigated the genomic population structure and the level of inbreeding of 185 river and 153 swamp buffaloes using runs of homozygosity (ROH). Analyses were carried out jointly and separately for the two buffalo types.

Results

The SNP bead chip detected in swamp about one-third of the SNPs identified in the river type. In total, 18,116 ROH were detected in the combined data set (17,784 SNPs), and 16,251 of these were unique. ROH were present in both buffalo types mostly detected (~ 59%) in swamp buffalo. The number of ROH per animal was larger and genomic inbreeding was higher in swamp than river buffalo. In the separated datasets (46,891 and 17,690 SNPs for river and swamp type, respectively), 19,760 and 10,581 ROH were found in river and swamp, respectively. The genes that map to the ROH islands are associated with the adaptation to the environment, fitness traits and reproduction.

Conclusions

Analysis of ROH features in the genome of the two water buffalo types allowed their genomic characterization and highlighted differences between buffalo types and between breeds. A large ROH island on chromosome 2 was shared between river and swamp buffaloes and contained genes that are involved in environmental adaptation and reproduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00616-3.

The Mammalian High Mobility Group Protein AT-Hook 2 (HMGA2): Biochemical and Biophysical Properties, and Its Association with Adipogenesis

The mammalian high-mobility-group protein AT-hook 2 (HMGA2) is a small DNA-binding protein and consists of three “AT-hook” DNA-binding motifs and a negatively charged C-terminal motif. It is a multifunctional nuclear protein directly linked to obesity, human height, stem cell youth, human intelligence, and tumorigenesis. Biochemical and biophysical studies showed that HMGA2 is an intrinsically disordered protein (IDP) and could form homodimers in aqueous buffer solution. The “AT-hook” DNA-binding motifs specifically bind to the minor groove of AT-rich DNA sequences and induce DNA-bending. HMGA2 plays an important role in adipogenesis most likely through stimulating the proliferative expansion of preadipocytes and also through regulating the expression of transcriptional factor Peroxisome proliferator-activated receptor γ (PPARγ) at the clonal expansion step from preadipocytes to adipocytes. Current evidence suggests that a main function of HMGA2 is to maintain stemness and renewal capacity of stem cells by which HMGA2 binds to chromosome and lock chromosome into a specific state, to allow the human embryonic stem cells to maintain their stem cell potency. Due to the importance of HMGA2 in adipogenesis and tumorigenesis, HMGA2 is considered a potential therapeutic target for anticancer and anti-obesity drugs. Efforts are taken to identify inhibitors targeting HMGA2.

NCAPG Dynamically Coordinates the Myogenesis of Fetal Bovine Tissue by Adjusting Chromatin Accessibility

NCAPG is a subunit of condensin I that plays a crucial role in chromatin condensation during mitosis. NCAPG has been demonstrated to be associated with farm animal growth traits. However, its role in regulating myoblast differentiation is still unclear. We used myoblasts derived from fetal bovine tissue as an in vitro model and found that NCAPG was expressed during myogenic differentiation in the cytoplasm and nucleus. Silencing NCAPG prolonged the mitosis and impaired the differentiation due to increased myoblast apoptosis. After 1.5 days of differentiation, silencing NCAPG enhanced muscle-specific gene expression. An assay for transposase-accessible chromatin- high throughput sequencing (ATAC-seq) revealed that silencing NCAPG altered chromatin accessibility to activating protein 1 (AP-1) and its subunits. Knocking down the expression of the AP-1 subunits fos-related antigen 2 (FOSL2) or junB proto-oncogene (JUNB) enhanced part of the muscle-specific gene expression. In conclusion, our data provide valuable evidence about NCAPG’s function in myogenesis, as well as its potential role in gene expression.

The LCORL Locus is under Selection in Large-Sized Pakistani Goat Breeds

Goat domestication and human selection for valued traits have formed diverse breeds with characteristic phenotypes. This process led to the fixation of causative genetic variants controlling breed-specific traits within regions of reduced genetic diversity-so-called "selection signatures". We previously reported an analysis of selection signatures based on pooled whole-genome sequencing data of 20 goat breeds and bezoar goats. In the present study, we reanalyzed the data and focused on a subset of eight Pakistani goat breeds (Angora, Barbari, Beetal, Dera Din Panah, Kamori, Nachi, Pahari, Teddy). We identified 749 selection signatures based on reduced heterozygosity in these breeds. A search for signatures that are shared across large-sized goat breeds revealed that five medium-to-large-sized Pakistani goat breeds had a common selection signature on chromosome 6 in a region harboring the LCORL gene, which has been shown to modulate height or body size in several mammalian species. Fine-mapping of the region confirmed that all five goat breeds with the selection signature were nearly fixed for the same haplotype in a ~191 kb region spanning positions 37,747,447-37,938,449. From the pool sequencing data, we identified a frame-shifting single base insertion into an isoform-specific exon of LCORL as a potential candidate causal variant mediating the size-increasing effect. If this preliminary result can be confirmed in independent replication studies, genotyping of this variant might be used to improve breeding programs and the selection for stature in goats.

HMGA Genes and Proteins in Development and Evolution

HMGA (high mobility group A) (HMGA1 and HMGA2) are small non-histone proteins that can bind DNA and modify chromatin state, thus modulating the accessibility of regulatory factors to the DNA and contributing to the overall panorama of gene expression tuning. In general, they are abundantly expressed during embryogenesis, but are downregulated in the adult differentiated tissues. In the present review, we summarize some aspects of their role during development, also dealing with relevant studies that have shed light on their functioning in cell biology and with emerging possible involvement of HMGA1 and HMGA2 in evolutionary biology.

Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs.

Complex Phenotypes: Mechanisms Underlying Variation in Human Stature

PURPOSE OF REVIEW

The goal of the review is to provide a comprehensive overview of the current understanding of the mechanisms underlying variation in human stature.

RECENT FINDINGS

Human height is an anthropometric trait that varies considerably within human populations as well as across the globe. Historically, much research focus was placed on understanding the biology of growth plate chondrocytes and how modifications to core chondrocyte proliferation and differentiation pathways potentially shaped height attainment in normal as well as pathological contexts. Recently, much progress has been made to improve our understanding regarding the mechanisms underlying the normal and pathological range of height variation within as well as between human populations, and today, it is understood to reflect complex interactions among a myriad of genetic, environmental, and evolutionary factors. Indeed, recent improvements in genetics (e.g., GWAS) and breakthroughs in functional genomics (e.g., whole exome sequencing, DNA methylation analysis, ATAC-sequencing, and CRISPR) have shed light on previously unknown pathways/mechanisms governing pathological and common height variation. Additionally, the use of an evolutionary perspective has also revealed important mechanisms that have shaped height variation across the planet. This review provides an overview of the current knowledge of the biological mechanisms underlying height variation by highlighting new research findings on skeletal growth control with an emphasis on previously unknown pathways/mechanisms influencing pathological and common height variation. In this context, this review also discusses how evolutionary forces likely shaped the genomic architecture of height across the globe.

Effect of LCORL gene polymorphism on body size traits in horse populations

The aim of this study was to determine polymorphism of LCORL gene in horse breeds and its association with body size. PCR-RFLP technique was performed using AluI for genotyping of 306 horses. Results showed that C is the rare allele in Iranian Breeds, because these horses have been used since ancient times as a courier and for war and archery, hence selection has done to benefit of spiky horses with medium body that need less food and are tireless. While, for foreign breeds; frequency of C allele was high that can be concluded these breeds used in fields, forests, and mines. A UPGMA dendrogram based on the Nei's standard genetic distance among studied breeds showed separate clusters for Iranian native and exotic breeds. Statistical association analysis of three observed genotypes with body size showed that there is an association between this polymorphism and body size criteria (p < 0.01). Overall, it can be concluded that studied mutation in LCORL gene can be used as candidate marker for improving body weight in horse.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Insights and Implications of Genome-Wide Association Studies of Height

CONTEXT

In the last decade, genome-wide association studies (GWASs) have catalyzed our understanding of the genetics of height and have identified hundreds of regions of the genome associated with adult height and other height-related body measurements.

EVIDENCE ACQUISITION

GWASs related to height were identified via PubMed search and a review of the GWAS catalog.

EVIDENCE SYNTHESIS

The GWAS results demonstrate that height is highly polygenic: that is, many thousands of genetic variants distributed across the genome each contribute to an individual's height. These height-associated regions of the genome are enriched for genes in known biological pathways involved in growth, such as fibroblast growth factor signaling, as well as for genes expressed in relevant tissues, such as the growth plate. GWASs can also uncover previously unappreciated biological pathways, such as the STC2/PAPPA/IGFBP4 pathway. The genes implicated by GWASs are often the same genes that are the genetic causes of Mendelian growth disorders or skeletal dysplasias, and GWAS results can provide complementary information about these disorders.

CONCLUSIONS

Here, we review the rationale behind GWASs and what we have learned from GWASs for height, including how it has enhanced our understanding of the underlying biology of human growth. We also highlight the implications of GWASs in terms of prediction of adult height and our understanding of Mendelian growth disorders.

A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers

The evolutionary and biological bases of the Central African "pygmy" phenotype, a characteristic of rainforest hunter-gatherers defined by reduced body size compared with neighboring farmers, remain largely unknown. Here, we perform a joint investigation in Central African hunter-gatherers and farmers of adult standing height, sitting height, leg length, and body mass index (BMI), considering 358 hunter-gatherers and 169 farmers with genotypes for 153,798 SNPs. In addition to reduced standing heights, hunter-gatherers have shorter sitting heights and leg lengths and higher sitting/standing height ratios than farmers and lower BMI for males. Standing height, sitting height, and leg length are strongly correlated with inferred levels of farmer genetic ancestry, whereas BMI is only weakly correlated, perhaps reflecting greater contributions of non-genetic factors to body weight than to height. Single- and multi-marker association tests identify one region and eight genes associated with hunter-gatherer/farmer status, and 24 genes associated with the height-related traits. Many of these genes have putative functions consistent with roles in determining their associated traits and the pygmy phenotype, and they include three associated with standing height in non-Africans (PRKG1, DSCAM, MAGI2). We find evidence that European height-associated SNPs or variants in linkage disequilibrium with them contribute to standing- and sitting-height determination in Central Africans, but not to the differential status of hunter-gatherers and farmers. These findings provide new insights into the biological basis of the pygmy phenotype, and they highlight the potential of cross-population studies for exploring the genetic basis of phenotypes that vary naturally across populations.

Admixture mapping and fine-mapping of birth weight loci in the Black Women's Health Study

Several genome-wide association studies (GWAS) have identified genetic variants associated with birth weight. To date, however, most GWAS of birth weight have focused primarily on European ancestry samples even though prevalence of low birth weight is higher among African-Americans. We conducted admixture mapping using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study, with the goal of identifying novel genomic regions where local African ancestry is associated with birth weight. In addition, we performed a replication analysis of 11 previously identified index single nucleotide polymorphisms (SNPs), and fine-mapped those genetic loci to identify better or new genetic variants associated with birth weight in African-Americans. We found that high African ancestry at 12q14 was associated with low birth weight, and we identified multiple independent birth weight-lowering variants in this genomic region. We replicated the association of a previous GWAS SNP in ADRB1 and our fine-mapping efforts suggested the presence of new birth weight-associated variants in ADRB1, HMGA2, and SLC2A4. Further studies are needed to determine whether birth weight-associated loci can in part explain race-associated birth weight disparities.

Genome-wide association study identifies loci and candidate genes for internal organ weights in Simmental beef cattle

Cattle internal organs as accessible raw materials have a long history of being widely used in beef processing, feed and pharmaceutical industry. These traits not only are of economic interest to breeders, but they are intrinsically linked to many valuable traits, such as growth, health, and productivity. Using the Illumina Bovine HD 770K SNP array, we performed a genome-wide association study for heart weight, liver weight, spleen weight, lung weight, and kidney weight in 1,217 Simmental cattle. In our research, 38 significant single nucleotide polymorphisms (SNPs) ( P < 1.49 × 10−6) were identified for five internal organ weight traits. These SNPs are within or near 13 genes, and some of them have been reported previously, including NDUFAF4, LCORL, BT.94996, SLIT2, FAM184B, LAP3, BBS12, MECOM, CD300LF, HSD17B3, TLR4, MXI1, and MB21D2. In addition, we detected four haplotype blocks on BTA6 containing 18 significant SNPs associated with spleen weight. Our results offer worthy insights into understanding the genetic mechanisms of internal organs' development, with potential application in breeding programs of Simmental beef cattle.

Height associated variants demonstrate assortative mating in human populations

Understanding human mating patterns, which can affect population genetic structure, is important for correctly modeling populations and performing genetic association studies. Prior studies of assortative mating in humans focused on trait similarity among spouses and relatives via phenotypic correlations. Limited research has quantified the genetic consequences of assortative mating. The degree to which the non-random mating influences genetic architecture remains unclear. Here, we studied genetic variants associated with human height to assess the degree of height-related assortative mating in European-American and African-American populations. We compared the inbreeding coefficient estimated using known height associated variants with that calculated from frequency matched sets of random variants. We observed significantly higher inbreeding coefficients for the height associated variants than from frequency matched random variants (P < 0.05), demonstrating height-related assortative mating in both populations.

Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations

An essential component of precision medicine is the ability to predict an individual's risk of disease based on genetic and non-genetic factors. For complex traits and diseases, assessing the risk due to genetic factors is challenging because it requires knowledge of both the identity of variants that influence the trait and their corresponding allelic effects. Although the set of risk variants and their allelic effects may vary between populations, a large proportion of these variants were identified based on studies in populations of European descent. Heterogeneity in genetic architecture underlying complex traits and diseases, while broadly acknowledged, remains poorly characterized. Ignoring such heterogeneity likely reduces predictive accuracy for minority individuals. In this study, we propose an approach, called XP-BLUP, which ameliorates this ethnic disparity by combining trans-ethnic and ethnic-specific information. We build a polygenic model for complex traits that distinguishes candidate trait-relevant variants from the rest of the genome. The set of candidate variants are selected based on studies in any human population, yet the allelic effects are evaluated in a population-specific fashion. Simulation studies and real data analyses demonstrate that XP-BLUP adaptively utilizes trans-ethnic information and can substantially improve predictive accuracy in minority populations. At the same time, our study highlights the importance of the continued expansion of minority cohorts.

Regulatory Variants Modulate Protein Kinase C α (PRKCA) Gene Expression in Human Heart

PURPOSE

Protein kinase C α (PRKCA) is involved in multiple functions and has been implicated in heart failure risks and treatment outcomes. This study aims to identify regulatory variants affecting PRKCA expression in human heart, and evaluate attributable risk of heart disease.

METHODS

mRNA expression quantitative trait loci (eQTLs) were extracted from the Genotype and Tissue Expression Project (GTEx). Allelic mRNA ratios were measured in 51 human heart tissues to identify cis-acting regulatory variants. Potential regulatory regions were tested with luciferase reporter gene assays and further evaluated in GTEx and genome-wide association studies.

RESULTS

Located in a region with robust enhancer activity in luciferase reporter assays, rs9909004 (T > C, minor allele frequency =0.47) resides in a haplotype displaying strong eQTLs for PRKCA in heart (p = 1.2 × 10-23). The minor C allele is associated with both decreased PRKCA mRNA expression and decreased risk of phenotypes characteristic of heart failure in GWAS analyses (QT interval p = 3.0 × 10-14). While rs9909004 is the likely regulatory variant, other variants in high linkage disequilibrium cannot be excluded. Distinct regulatory variants appear to affect expression in other tissues.

CONCLUSIONS

The haplotype carrying rs9909004 influences PRKCA expression in the heart and is associated with traits linked to heart failure, potentially affecting therapy of heart failure.

Low-expression of TMEM100 is associated with poor prognosis in non-small-cell lung cancer

Transmembrane protein 100 (TMEM100) was first identified as a transcript from the mouse genome. Recent studies have demonstrated that TMEM100 is involved in hepatocellular carcinoma (HCC) malignancy. However, the distribution and clinical significance of TMEM100 in non-small-cell lung carcinoma (NSCLC) remains poorly understood. This study aims to explore the significance of TMEM100 expression in NSCLC. We found that TMEM100 expression was significantly reduced in NSCLC tissues when compared with that in adjacent normal lung tissues (P<0.001). Kaplan-Meier survival analysis showed that overall survival of patients with lower expressions of TMEM100 was significantly shorter (n=152, P<0.05). In addition, TMEM100 overexpression in NSCLC cell lines inhibited cell proliferation in vitro and in vivo. Transwell migration and invasion assay showed that TMEM100 significantly suppressed the migration and invasion of NSCLC cell lines. In contrast, knocking down TMEM100 promoted NSCLC proliferation and migration. Finally, we found that TMEM100 worked as a cancer suppressor gene mainly by inhibiting the TNF signaling pathway. In conclusion, TMEM100 acted as a tumor suppressor in NSCLC and may prove to be a potential prognostic biomarker and therapeutic target for NSCLC.

Identification of a functional genetic variant driving racially dimorphic platelet gene expression of the thrombin receptor regulator, PCTP

Platelet activation in response to stimulation of the Protease Activated Receptor 4 (PAR4) receptor differs by race. One factor that contributes to this difference is the expression level of Phosphatidylcholine Transfer Protein (PCTP), a regulator of platelet PAR4 function. We have conducted an expression Quantitative Trait Locus (eQTL) analysis that identifies single nucleotide polymorphisms (SNPs) linked to the expression level of platelet genes. This analysis revealed 26 SNPs associated with the expression level of PCTP at genome-wide significance (p < 5×10^-8). Using annotation from ENCODE and other public data we prioritised one of these SNPs, rs2912553, for functional testing. The allelic frequency of rs2912553 is racially-dimorphic, in concordance with the racially differential expression of PCTP. Reporter gene assays confirmed that the single nucleotide change caused by rs2912553 altered the transcriptional potency of the surrounding genomic locus. Electromobility shift assays, luciferase assays, and overexpression studies indicated a role for the megakaryocytic transcription factor GATA1. In summary, we have integrated multi-omic data to identify and functionalise an eQTL. This, along with the previously described relationship between PCTP and PAR4 function, allows us to characterise a genotype-phenotype relationship through the mechanism of gene expression.

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods.

AVAILABILITY AND IMPLEMENTATION

The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Serum lipid changes following the onset of depressive symptoms in postmenopausal women

A cross-sectional association between depression and serum low-density lipoprotein cholesterol (LDL-c) has been noted in psychiatric literature, raising the question of temporality: does low LDL-c predict depression, does depression lead to changes in LDL-c levels, or is this relationship bidirectional? In a previous longitudinal analysis of postmenopausal women ages 50-79 who participated in the Women's Health Initiative (WHI), we detected an association between low LDL-c and the subsequent onset of depressive symptoms (HR=1.25, 95% CI 1.05-1.49, p=0.01). This current study uses the WHI cohort to explore the question of temporality in the opposite direction, examining the influence of depressive symptoms on subsequent changes in LDL-c levels. This study provides no evidence to suggest an association between depression and subsequent changes in LDL-c level (-2.78mg/dL, 95% CI=-7.49 to 1.92, p=0.25), nor was any association detected for total cholesterol, HDL, or triglyceride changes over time. Further, this study demonstrates that the relationship between depression and serum LDL changes is not mediated by changes in weight, exercise, or energy intake.

Polymorphisms in ten candidate genes are associated with conformational and locomotive traits in Spanish Purebred horses

The Spanish Purebred horses, also known as Andalusian horses, compete to the highest standards in international dressage events. Gait and conformation could be used as early selection criteria to detect young horses with promising dressage ability. Although the genetic background of equine size variation has been recently uncovered, the genetic basis of horse conformational and locomotive traits is not known, hampered by the complex genetic architecture underlying quantitative traits and the lack of phenotypic data. The aim of this study was to validate the loci associated with size in 144 Spanish Purebred horses, and to seek novel associations between loci previously associated with the development of osteochondrosis (OC) lesions and 20 conformational and locomotive traits. Ten loci were associated with different conformational and locomotive traits (LCORL/NCAPG, HMGA2, USP31, MECR, COL24A1, MGP, FAM184B, PTH1R, KLF3 and SGK1), and the LCORL/NCAPG association with size in the Spanish Purebred horse was validated. Except for HMGA2, all polymorphisms seem to influence both the prevalence of OC lesions and morphological characters, supporting the link between conformation and OC. Also, the implication of most genes in either immune and inflammatory responses and cellular growth, or ossification processes, reinforces the role that these mechanisms have in the aetiology of OC, as well as their reflection on the general conformation of the individual. These polymorphisms could be used in marker-assisted selection (MAS) programmes to improve desirable conformational traits, but taking into account their possible detrimental effect on OC prevalence.

Association Study of GWAS-Derived Loci with Height in Brazilian Children: Importance of MAP3K3, MMP24 and IGF1R Polymorphisms for Height Variation

BACKGROUND/AIM

The single nucleotide polymorphisms (SNPs) rs2282978 (CDK6), rs2425019 (MMP24), rs8081612 (MAP3K3), rs2871865 (IGF1R) and rs3782415 (SOCS2) were among the SNPs most strongly associated with height in a meta-analysis of 47 genome-wide association studies (GWAS) involving 114,223 adults from six ethnic groups. The present study aimed to examine associations between these SNPs and height in Brazilian children.

METHODS

Cross-sectional heights of 1,008 healthy unrelated 4.4- to 9.7-year-old children were evaluated. All genotypes were determined by allele-specific polymerase chain reactions. Height standard deviation scores (SDS) were generated for this population and regressed on allele counts. Linear regressions were performed to estimate the effect of individual SNPs or a polygenic allelic score on height.

RESULTS

The T allele of rs8081612 (MAP3K3), the C allele of rs2871865 (IGF1R) and the G allele of rs2425019 (MMP24) were significantly associated with a 0.091-SDS greater height (95% CI 0.089-0.093, p = 0.001) by polygenic analysis. The mean height SDS difference between children with 2 'tall' alleles and children with 4 'tall' alleles was 0.24 SDS (95% CI 0.05-0.43, p = 0.01). The observed allelic effect is consistent with that found in previous GWAS.

CONCLUSIONS

Polymorphisms in MAP3K3, MMP24 and IGF1R act additively on height in children of an admixed population. These results demonstrate the importance of these loci for children's height.

Four Susceptibility Loci for Gallstone Disease Identified in a Meta-analysis of Genome-Wide Association Studies

BACKGROUND & AIMS

A genome-wide association study (GWAS) of 280 cases identified the hepatic cholesterol transporter ABCG8 as a locus associated with risk for gallstone disease, but findings have not been reported from any other GWAS of this phenotype. We performed a large-scale, meta-analysis of GWASs of individuals of European ancestry with available prior genotype data, to identify additional genetic risk factors for gallstone disease.

METHODS

We obtained per-allele odds ratio (OR) and standard error estimates using age- and sex-adjusted logistic regression models within each of the 10 discovery studies (8720 cases and 55,152 controls). We performed an inverse variance weighted, fixed-effects meta-analysis of study-specific estimates to identify single-nucleotide polymorphisms that were associated independently with gallstone disease. Associations were replicated in 6489 cases and 62,797 controls.

RESULTS

We observed independent associations for 2 single-nucleotide polymorphisms at the ABCG8 locus: rs11887534 (OR, 1.69; 95% confidence interval [CI], 1.54-1.86; P = 2.44 × 10(-60)) and rs4245791 (OR, 1.27; P = 1.90 × 10(-34)). We also identified and/or replicated associations for rs9843304 in TM4SF4 (OR, 1.12; 95% CI, 1.08-1.16; P = 6.09 × 10(-11)), rs2547231 in SULT2A1 (encodes a sulfoconjugation enzyme that acts on hydroxysteroids and cholesterol-derived sterol bile acids) (OR, 1.17; 95% CI, 1.12-1.21; P = 2.24 × 10(-10)), rs1260326 in glucokinase regulatory protein (OR, 1.12; 95% CI, 1.07-1.17; P = 2.55 × 10(-10)), and rs6471717 near CYP7A1 (encodes an enzyme that catalyzes conversion of cholesterol to primary bile acids) (OR, 1.11; 95% CI, 1.08-1.15; P = 8.84 × 10(-9)). Among individuals of African American and Hispanic American ancestry, rs11887534 and rs4245791 were associated positively with gallstone disease risk, whereas the association for the rs1260326 variant was inverse.

CONCLUSIONS

In this large-scale GWAS of gallstone disease, we identified 4 loci in genes that have putative functions in cholesterol metabolism and transport, and sulfonylation of bile acids or hydroxysteroids.

Novel roles of TMEM100: inhibition metastasis and proliferation of hepatocellular carcinoma

Transmembrane protein 100 (TMEM100) was activated by ALK1/TGF-β signaling. We found that TMEM100 was decreased in hepatocellular carcinoma (HCC) tissues and in highly metastatic cell lines. Overexpressed of TMEM100 inhibited invasion, migration and proliferation. Low levels of TMEM100 were associated with cirrhosis, tumor size, Tumor nodule number, TNM stage, BCLC stage, Edmondson-Steiner Stage and vein invasion. Furthermore, TMEM100 was an independent risk factor for overall survival (P = 0.03) and disease-free survival (P = 0.019). The current findings suggest that TMEM100 functions as a tumor suppressor in HCC metastasis and proliferation.

Genome-wide association reveals QTL for growth, bone and in vivo carcass traits as assessed by computed tomography in Scottish Blackface lambs

BACKGROUND

Improving meat quality including taste and tenderness is critical to the protection and development of markets for sheep meat. Phenotypic selection for such measures of meat quality is constrained by the fact that these parameters can only be measured post-slaughter. Carcass composition has an impact on meat quality and can be measured on live animals using advanced imaging technologies such as X-ray computed tomography (CT). Since carcass composition traits are heritable, they are potentially amenable to improvement through marker-assisted and genomic selection. We conducted a genome-wide association study (GWAS) on about 600 Scottish Blackface lambs for which detailed carcass composition phenotypes, including bone, fat and muscle components, had been captured using CT and which were genotyped for ~40,000 single nucleotide polymorphisms (SNPs) using the Illumina OvineSNP50 chip.

RESULTS

We confirmed that the carcass composition traits were heritable with moderate to high (0.19-0.78) heritabilities. The GWAS analyses revealed multiple SNPs and quantitative trait loci (QTL) that were associated with effects on carcass composition traits and were significant at the genome-wide level. In particular, we identified a region on ovine chromosome 6 (OAR6) associated with bone weight and bone area that harboured SNPs with p values of 5.55 × 10(-8) and 2.63 × 10(-9), respectively. The same region had effects on fat area, fat density, fat weight and muscle density. We identified plausible positional candidate genes for these OAR6 QTL. We also detected a SNP that reached the genome-wide significance threshold with a p value of 7.28 × 10(-7) and was associated with muscle density on OAR1. Using a regional heritability mapping approach, we also detected regions on OAR3 and 24 that reached genome-wide significance for bone density.

CONCLUSIONS

We identified QTL on OAR1, 3, 24 and particularly on OAR6 that are associated with effects on muscle, fat and bone traits. Based on available evidence that indicates that these traits are genetically correlated with meat quality traits, these associated SNPs have potential applications in selective breeding for improved meat quality. Further research is required to determine whether the effects associated with the OAR6 QTL are caused by a single gene or several closely-linked genes.

Longitudinal study of low serum LDL cholesterol and depressive symptom onset in postmenopause

OBJECTIVE

The aim of this study was to characterize the relationship between serum low-density lipoprotein cholesterol (LDL-c) and subsequent depressive symptoms onset in postmenopausal women. We secondarily assessed serum high-density lipoprotein (HDL-c), total cholesterol, and triglycerides.

METHOD

This population-based prospective cohort study utilizes data from 24,216 women between 50 and 79 years of age who were participants of the Women's Health Initiative, which originally ran from 1993 to 2005 and has since incorporated 2 extension studies, with the most recent culminating in 2015. Fasting lipids were measured for all participants at baseline and for a subset through 6 years of follow-up. Depressive symptoms were characterized using the Burnam 8-item scale for depressive disorders (Center for Epidemiologic Studies-Depression/Diagnostic Interview Schedule short form) at baseline and during follow-up, using a cut point of 0.06 to indicate presence of depressive symptoms.

RESULTS

The lowest quintile of LDL-c was associated with an increased risk of subsequent depressive symptoms (hazard ratio [HR] = 1.25, 95% CI = 1.05-1.49, P = .01), and follow-up analyses demonstrated that the elevated risk appeared to be confined to the lowest decile (LDL-c < 100 mg/dL). Further, this elevated risk was moderated by lipid-lowering drug treatment. Elevated risk was demonstrated among those who reported no lipid-lowering medication use (HR = 1.23, 95% CI = 1.03-1.47, P = .02), but not among those reporting use (HR = 0.65, 95% CI = 0.18-2.29, P = .50).

CONCLUSIONS

Among postmenopausal women, untreated serum LDL-c below 100 mg/dL was associated with an increased risk of developing depressive symptoms. No excess risk was observed in those attaining LDL-c < 100 mg/dL with lipid-lowering therapy. These findings have important implications for risk assessment, treatment considerations, and mechanistic insight.

Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)

Background

Despite heritability estimates of 40–70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI.

Methods

Using genotypic data from 18,686 individuals across five study cohorts – ARIC, CARDIA, FHS, CHS, MESA – we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of BMI. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects non-linear interactions associated with a quantitative trait.

Results

We identified seven novel, epistatic models with a Bonferroni corrected p-value of association < 0.1. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). Moreover, we found an 8.8 % increase in the variance in BMI explained by these seven SNP-SNP interactions, beyond what is explained by the main effects of an index FTO SNP and the SNPs within these interactions. We also replicated one of these interactions and 58 proxy SNP-SNP models representing it in an independent dataset from the eMERGE study.

Conclusion

This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-015-0074-0) contains supplementary material, which is available to authorized users.

FTO association and interaction with time spent sitting

Background/Objectives

Multiple studies have revealed an interaction between a variant in the FTO gene and self-reported physical activity on body-mass index (BMI). Physical inactivity, such as time spent sitting (TSS) has recently gained attention as an important risk factor for obesity and related diseases. It is possible that FTO interacts with TSS to affect BMI, and/or that FTO's putative effect on BMI is mediated through TSS.

Subjects/Methods

We tested these hypotheses in two cohorts of the Framingham Heart Study (FHS) (Offspring: n=3,430, and 3^rd Generation: n=3,888), and attempted to replicate our results in the Women's Health Initiative (WHI) (n= 4,756). Specifically, we examined whether an association exists between FTO and self-reported TSS, and whether an interaction exists between FTO and TSS on BMI, while adjusting for several important covariates such as physical activity.

Results

In FHS, we find a significant positive association between the BMI-increasing FTO allele and TSS. We find a similar trend in WHI. Mediation analyses suggest that the effect of FTO on BMI is mediated through TSS. In FHS, we find a significant interaction of FTO and TSS on BMI, whereby the association of TSS with BMI is greatest among those with more FTO risk alleles. In WHI, we also find a significant interaction, although the direction is opposite to that in FHS. In a meta-analysis of the two datasets, there is no net interaction of FTO with TSS on BMI.

Conclusions

Our study suggests that FTO exerts its effect on BMI, at least partly, through energy expenditure mechanisms such as TSS. Further research into the intersection of genetics, sedentary behavior, and obesity-related outcomes is warranted.

PLAG1 and NCAPG-LCORL in livestock

A recent progress on stature genetics has revealed simple genetic architecture in livestock animals in contrast to that in humans. PLAG1 and/or NCAPG‐LCORL, both of which are known as a locus for adult human height, have been detected for association with body weight/height in cattle and horses, and for selective sweep in dogs and pigs. The findings indicate a significant impact of these loci on mammalian growth or body size and usefulness of the natural variants for selective breeding. However, association with an unfavorable trait, such as late puberty or risk for a neuropathic disease, was also reported for the respective loci, indicating an importance to discriminate between causality and association. Here I review the recent findings on quantitative trait loci (QTL) for stature in livestock animals, mainly focusing on the PLAG1 and NCAPG‐LCORL loci. I also describe our recent efforts to identify the causative variation for the third major locus for carcass weight in Japanese Black cattle.