Hundreds of variants clustered in genomic loci and biological pathways affect human height

Genomic Prediction Informed by Biological Processes Expands Our Understanding of the Genetic Architecture Underlying Free Amino Acid Traits in Dry Arabidopsis Seeds

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.

Genome-wide association study of self-reported walking pace suggests beneficial effects of brisk walking on health and survival

Walking is a simple form of exercise, widely promoted for its health benefits. Self-reported walking pace has been associated with a range of cardiorespiratory and cancer outcomes, and is a strong predictor of mortality. Here we perform a genome-wide association study of self-reported walking pace in 450,967 European ancestry UK Biobank participants. We identify 70 independent associated loci (P < 5 × 10^-8), 11 of which are novel. We estimate the SNP-based heritability as 13.2% (s.e. = 0.21%), reducing to 8.9% (s.e. = 0.17%) with adjustment for body mass index. Significant genetic correlations are observed with cardiometabolic, respiratory and psychiatric traits, educational attainment and all-cause mortality. Mendelian randomization analyses suggest a potential causal link of increasing walking pace with a lower cardiometabolic risk profile. Given its low heritability and simple measurement, these findings suggest that self-reported walking pace is a pragmatic target for interventions aiming for general benefits on health.

A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank

The UK Biobank is a very large, prospective population-based cohort study across the United Kingdom. It provides unprecedented opportunities for researchers to investigate the relationship between genotypic information and phenotypes of interest. Multiple regression methods, compared with genome-wide association studies (GWAS), have already been showed to greatly improve the prediction performance for a variety of phenotypes. In the high-dimensional settings, the lasso, since its first proposal in statistics, has been proved to be an effective method for simultaneous variable selection and estimation. However, the large-scale and ultrahigh dimension seen in the UK Biobank pose new challenges for applying the lasso method, as many existing algorithms and their implementations are not scalable to large applications. In this paper, we propose a computational framework called batch screening iterative lasso (BASIL) that can take advantage of any existing lasso solver and easily build a scalable solution for very large data, including those that are larger than the memory size. We introduce snpnet, an R package that implements the proposed algorithm on top of glmnet and optimizes for single nucleotide polymorphism (SNP) datasets. It currently supports ℓ1-penalized linear model, logistic regression, Cox model, and also extends to the elastic net with ℓ1/ℓ2 penalty. We demonstrate results on the UK Biobank dataset, where we achieve competitive predictive performance for all four phenotypes considered (height, body mass index, asthma, high cholesterol) using only a small fraction of the variants compared with other established polygenic risk score methods.

Downregulation of the GHRH/GH/IGF1 axis in a mouse model of Börjeson-Forssman-Lehman syndrome

Börjeson-Forssman-Lehmann syndrome (BFLS) is an intellectual disability and endocrine disorder caused by plant homeodomain finger 6 (PHF6) mutations. Individuals with BFLS present with short stature. We report a mouse model of BFLS, in which deletion of Phf6 causes a proportional reduction in body size compared with control mice. Growth hormone (GH) levels were reduced in the absence of PHF6. Phf6 ^{- /Y} animals displayed a reduction in the expression of the genes encoding GH-releasing hormone (GHRH) in the brain, GH in the pituitary gland and insulin-like growth factor 1 (IGF1) in the liver. Phf6 deletion specifically in the nervous system caused a proportional growth defect, indicating a neuroendocrine contribution to the phenotype. Loss of suppressor of cytokine signaling 2 (SOCS2), a negative regulator of growth hormone signaling partially rescued body size, supporting a reversible deficiency in GH signaling. These results demonstrate that PHF6 regulates the GHRH/GH/IGF1 axis.

Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease

BACKGROUND

The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms.

OBJECTIVE

The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy.

METHODS

First, we took advantage of a dense module search algorithm to identify modules enriched by genetic association signals in a protein-protein interaction network. Next, we performed statistical evaluation to the modules identified by dense module search, including a normalization process to adjust the topological bias in the network, a replication test to ensure the modules were not found randomly , and a permutation test to evaluate unbiased associations between the modules and amyloid imaging phenotype. Finally, topological analysis, module similarity tests and functional enrichment analysis were performed for the identified modules.

RESULTS

We identified 24 consensus modules enriched by robust genetic signals in a genome-wide association analysis. The results not only validated several previously reported AD genes (APOE, APP, TOMM40, DDAH1, PARK2, ATP5C1, PVRL2, ELAVL1, ACTN1 and NRF1), but also nominated a few novel genes (ABL1, ABLIM2) that have not been studied in Alzheimer's disease but have shown associations with other neurodegenerative diseases.

CONCLUSION

The identified genes, consensus modules and enriched pathways may provide important clues to future research on the neurobiology of Alzheimer's disease and suggest potential therapeutic targets.

Novel Mutations and Genes That Impact on Growth in Short Stature of Undefined Aetiology: The EPIGROW Study

BACKGROUND

Children with short stature of undefined aetiology (SS-UA) may have undiagnosed genetic conditions.

PURPOSE

To identify mutations causing short stature (SS) and genes related to SS, using candidate gene sequence data from the European EPIGROW study.

METHODS

First, we selected exonic single nucleotide polymorphisms (SNPs), in cases and not controls, with minor allele frequency (MAF) < 2%, whose carriage fitted the mode of inheritance. Known mutations were identified using Ensembl and gene-specific databases. Variants were classified as pathogenic, likely pathogenic, or variant of uncertain significance using criteria from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. If predicted by ≥ 5/10 algorithms (eg, Polyphen2) to be deleterious, this was considered supporting evidence of pathogenicity. Second, gene-based burden testing determined the difference in SNP frequencies between cases and controls across all and then rare SNPs. For genotype/phenotype relationships, we used PLINK, based on haplotype, MAF > 2%, genotype present in > 75%, and Hardy Weinberg equilibrium P > 10-4.

RESULTS

First, a diagnostic yield of 10% (27/263) was generated by 2 pathogenic (nonsense in ACAN) and a further 25 likely pathogenic mutations, including previously known missense mutations in FANCB, IGFIR, MMP13, NPR2, OBSL1, and PTPN11. Second, genes related to SS: all methods identified PEX2. Another 7 genes (BUB1B, FANCM, CUL7, FANCA, PTCH1, TEAD3, BCAS3) were identified by both gene-based approaches and 6 (A2M, EFEMP1, PRKCH, SOS2, RNF135, ZBTB38) were identified by gene-based testing for all SNPs and PLINK.

CONCLUSIONS

Such panels improve diagnosis in SS-UA, extending known disease phenotypes. Fourteen genes related to SS included some known to cause growth disorders as well as novel targets.

Penalized regression and model selection methods for polygenic scores on summary statistics

Polygenic scores quantify the genetic risk associated with a given phenotype and are widely used to predict the risk of complex diseases. There has been recent interest in developing methods to construct polygenic risk scores using summary statistic data. We propose a method to construct polygenic risk scores via penalized regression using summary statistic data and publicly available reference data. Our method bears similarity to existing method LassoSum, extending their framework to the Truncated Lasso Penalty (TLP) and the elastic net. We show via simulation and real data application that the TLP improves predictive accuracy as compared to the LASSO while imposing additional sparsity where appropriate. To facilitate model selection in the absence of validation data, we propose methods for estimating model fitting criteria AIC and BIC. These methods approximate the AIC and BIC in the case where we have a polygenic risk score estimated on summary statistic data and no validation data. Additionally, we propose the so-called quasi-correlation metric, which quantifies the predictive accuracy of a polygenic risk score applied to out-of-sample data for which we have only summary statistic information. In total, these methods facilitate estimation and model selection of polygenic risk scores on summary statistic data, and the application of these polygenic risk scores to out-of-sample data for which we have only summary statistic information. We demonstrate the utility of these methods by applying them to GWA studies of lipids, height, and lung cancer.

Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F₂ resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1-6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.

The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits

Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.

Regulation of cellular sterol homeostasis by the oxygen responsive noncoding RNA lincNORS

We hereby provide the initial portrait of lincNORS, a spliced lincRNA generated by the MIR193BHG locus, entirely distinct from the previously described miR-193b-365a tandem. While inducible by low O₂ in a variety of cells and associated with hypoxia in vivo, our studies show that lincNORS is subject to multiple regulatory inputs, including estrogen signals. Biochemically, this lincRNA fine-tunes cellular sterol/steroid biosynthesis by repressing the expression of multiple pathway components. Mechanistically, the function of lincNORS requires the presence of RALY, an RNA-binding protein recently found to be implicated in cholesterol homeostasis. We also noticed the proximity between this locus and naturally occurring genetic variations highly significant for sterol/steroid-related phenotypes, in particular the age of sexual maturation. An integrative analysis of these variants provided a more formal link between these phenotypes and lincNORS, further strengthening the case for its biological relevance.

Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock

Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.

The Pathophysiological Significance of Fibulin-3

Fibulin-3 (also known as EGF-containing fibulin extracellular matrix protein 1 (EFEMP1)) is a secreted extracellular matrix glycoprotein, encoded by the EFEMP1 gene that belongs to the eight-membered fibulin protein family. It has emerged as a functionally unique member of this family, with a diverse array of pathophysiological associations predominantly centered on its role as a modulator of extracellular matrix (ECM) biology. Fibulin-3 is widely expressed in the human body, especially in elastic-fibre-rich tissues and ocular structures, and interacts with enzymatic ECM regulators, including tissue inhibitor of metalloproteinase-3 (TIMP-3). A point mutation in EFEMP1 causes an inherited early-onset form of macular degeneration called Malattia Leventinese/Doyne honeycomb retinal dystrophy (ML/DHRD). EFEMP1 genetic variants have also been associated in genome-wide association studies with numerous complex inherited phenotypes, both physiological (namely, developmental anthropometric traits) and pathological (many of which involve abnormalities of connective tissue function). Furthermore, EFEMP1 expression changes are implicated in the progression of numerous types of cancer, an area in which fibulin-3 has putative significance as a therapeutic target. Here we discuss the potential mechanistic roles of fibulin-3 in these pathologies and highlight how it may contribute to the development, structural integrity, and emergent functionality of the ECM and connective tissues across a range of anatomical locations. Its myriad of aetiological roles positions fibulin-3 as a molecule of interest across numerous research fields and may inform our future understanding and therapeutic approach to many human diseases in clinical settings.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F₂ generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F₀, F₂, F₈, and F₉ generations of AIL and demonstrate that the population of the F₉ generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F₂ generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds

Background

Thousands of years of natural and artificial selection have resulted in indigenous cattle breeds that are well-adapted to the environmental challenges of their local habitat and thereby are considered as valuable genetic resources. Understanding the genetic background of such adaptation processes can help us design effective breeding objectives to preserve local breeds and improve commercial cattle. To identify regions under putative selection, GGP HD 150 K single nucleotide polymorphism (SNP) arrays were used to genotype 106 individuals representing five Swedish breeds i.e. native to different regions and covering areas with a subarctic cold climate in the north and mountainous west, to those with a continental climate in the more densely populated south regions.

Results

Five statistics were incorporated within a framework, known as de-correlated composite of multiple signals (DCMS) to detect signatures of selection. The obtained p-values were adjusted for multiple testing (FDR < 5%), and significant genomic regions were identified. Annotation of genes in these regions revealed various verified and novel candidate genes that are associated with a diverse range of traits, including e.g. high altitude adaptation and response to hypoxia (DCAF8, PPP1R12A, SLC16A3, UCP2, UCP3, TIGAR), cold acclimation (AQP3, AQP7, HSPB8), body size and stature (PLAG1, KCNA6, NDUFA9, AKAP3, C5H12orf4, RAD51AP1, FGF6, TIGAR, CCND2, CSMD3), resistance to disease and bacterial infection (CHI3L2, GBP6, PPFIBP1, REP15, CYP4F2, TIGD2, PYURF, SLC10A2, FCHSD2, ARHGEF17, RELT, PRDM2, KDM5B), reproduction (PPP1R12A, ZFP36L2, CSPP1), milk yield and components (NPC1L1, NUDCD3, ACSS1, FCHSD2), growth and feed efficiency (TMEM68, TGS1, LYN, XKR4, FOXA2, GBP2, GBP5, FGD6), and polled phenotype (URB1, EVA1C).

Conclusions

We identified genomic regions that may provide background knowledge to understand the mechanisms that are involved in economic traits and adaptation to cold climate in cattle. Incorporating p-values of different statistics in a single DCMS framework may help select and prioritize candidate genes for further analyses.

Genome-wide association study for circulating fibroblast growth factor 21 and 23

Fibroblast growth factors (FGFs) 21 and 23 are recently identified hormones regulating metabolism of glucose, lipid, phosphate and vitamin D. Here we conducted a genome-wide association study (GWAS) for circulating FGF21 and FGF23 concentrations to identify their genetic determinants. We enrolled 5,000 participants from Taiwan Biobank for this GWAS. After excluding participants with diabetes mellitus and quality control, association of single nucleotide polymorphisms (SNPs) with log-transformed FGF21 and FGF23 serum concentrations adjusted for age, sex and principal components of ancestry were analyzed. A second model additionally adjusted for body mass index (BMI) and a third model additionally adjusted for BMI and estimated glomerular filtration rate (eGFR) were used. A total of 4,201 participants underwent GWAS analysis. rs67327215, located within RGS6 (a gene involved in fatty acid synthesis), and two other SNPs (rs12565114 and rs9520257, located between PHC2-ZSCAN20 and ARGLU1-FAM155A respectively) showed suggestive associations with serum FGF21 level (P = 6.66 × 10^–7, 6.00 × 10^–7 and 6.11 × 10^–7 respectively). The SNPs rs17111495 and rs17843626 were significantly associated with FGF23 level, with the former near PCSK9 gene and the latter near HLA-DQA1 gene (P = 1.04 × 10^–10 and 1.80 × 10^–8 respectively). SNP rs2798631, located within the TGFB2 gene, was suggestively associated with serum FGF23 level (P = 4.97 × 10^–7). Additional adjustment for BMI yielded similar results. For FGF23, further adjustment for eGFR had similar results. We conducted the first GWAS of circulating FGF21 levels to date. Novel candidate genetic loci associated with circulating FGF21 or FGF23 levels were found. Further replication and functional studies are needed to support our findings.

Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits

In depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species.

A Mendelian Randomization Study on Infant Length and Type 2 Diabetes Mellitus Risk

OBJECTIVE

Infant length (IL) is a positively associated phenotype of type 2 diabetes mellitus (T2DM), but the causal relationship of which is still unclear. Here, we applied a Mendelian randomization (MR) study to explore the causal relationship between IL and T2DM, which has the potential to provide guidance for assessing T2DM activity and T2DM- prevention in young at-risk populations.

MATERIALS AND METHODS

To classify the study, a two-sample MR, using genetic instrumental variables (IVs) to explore the causal effect was applied to test the influence of IL on the risk of T2DM. In this study, MR was carried out on GWAS data using 8 independent IL SNPs as IVs. The pooled odds ratio (OR) of these SNPs was calculated by the inverse-variance weighted method for the assessment of the risk the shorter IL brings to T2DM. Sensitivity validation was conducted to identify the effect of individual SNPs. MR-Egger regression was used to detect pleiotropic bias of IVs.

RESULTS

The pooled odds ratio from the IVW method was 1.03 (95% CI 0.89-1.18, P = 0.0785), low intercept was -0.477, P = 0.252, and small fluctuation of ORs ranged from -0.062 ((0.966 - 1.03) / 1.03) to 0.05 ((1.081 - 1.03) / 1.03) in leave-one-out validation.

CONCLUSION

We validated that the shorter IL causes no additional risk to T2DM. The sensitivity analysis and the MR-Egger regression analysis also provided adequate evidence that the above result was not due to any heterogeneity or pleiotropic effect of IVs.

Association between systemic sclerosis and risk of lung cancer: results from a pool of cohort studies and Mendelian randomization analysis

BACKGROUND

Population-based cohort studies have indicated that systemic sclerosis (SSc) may be associated with an increased risk of lung cancer. However, there are few studies that comprehensively investigate their correlation and the causal effect remains unknown.

METHODS

A systematic search of PubMed, Web of Science, Cochrane Library and Embase from the inception dates to December 1, 2019 was carried out. Meta-analysis was performed to calculate odds ratio (OR) and corresponding 95% confidence interval (CI) using random-effects models. Subgroup analyses were performed regarding gender. Two-sample Mendelian randomization (MR) was carried out with summary data from published genome-wide association studies of SSc (Neale Lab, 3871 individuals; UK Biobank, 463,315 individuals) and lung cancer (International Lung Cancer Consortium, 27,209 individuals; UK Biobank, 508,977 individuals). Study-specific estimates were summarized using inverse variance-weighted, weighted median, and MR-Egger method.

RESULTS

Through meta-analysis of 10 population-based cohort studies involving 12,218 patients, we observed a significantly increased risk of lung cancer among patients with SSc (OR 2.80, 95% CI 1.55-5.03). In accordance with subgroup analysis, male patients (OR 4.11, 95% CI 1.92-8.79) had a 1.5-fold higher lung cancer risk compared with female patients (OR 2.73, 95% CI 1.41-5.27). However, using a score of 11 SSc-related single nucleotide polymorphisms (p < 5*10^-8) as instrumental variables, the MR study did not support a causality between SSc and lung cancer (OR 1.001, 95% CI 0.929-1.100, p = 0.800). Specifically, subgroup MR analyses indicated that SSc was not associated with increased risks of non-small-cell lung cancer (OR 1.000, 95% CI 0.999-1.000, p = 0.974), including lung adenocarcinoma (OR 0.996, 95% CI 0.906-1.094, p = 0.927), squamous cell lung carcinoma (OR 1.034, 95% CI 0.937-1.140, p = 0.507), nor small-cell lung cancer (OR 1.000, 95% CI 0.999-1.000, p = 0.837).

CONCLUSIONS

This study indicated an increased risk of lung cancer among patients with SSc by meta-analysis, whereas the MR study did not support a causality between the two diseases. Further studies are warranted to investigate the factors underlying the attribution of SSc to lung cancer risk.

Pregnancy-associated plasma proteins and Stanniocalcin-2 - Novel players controlling IGF-I physiology

IGF-I was originally discovered as a GH-dependent growth factor stimulating longitudinal growth. Currently, however, it has become evident that the biological activities of IGF-I extend well beyond those of a simple growth factor and impact such processes as insulin sensitivity, aging, cancer and cardiovascular disease. The vast majority of IGF-I is tightly bound to IGF-binding proteins (IGFBPs), which renders IGF-I unable to stimulate the IGF-I receptor (IGF-IR) in vivo. This binding means that liberation of IGF-I from the IGFBPs is an important step controlling IGF-I action. In this context, IGFBP-cleaving enzymes appear to play a key role. Enzymatic cleavage of the IGFBPs markedly lowers their ligand affinity, and as a consequence, IGF-I becomes liberated and hence available for stimulation of the IGF-IR. Two of the best-characterized IGFBP-cleaving enzymes are pregnancy-associated plasma protein-A (PAPP-A) and its paralog PAPP-A2. The two enzymes (often referred to as pappalysins) regulate the liberation of IGF-I in a highly controlled manner. PAPP-A is believed to act predominantly in tissues, serving to liberate IGF-I at the cell surface in close proximity to the IGF-IR. In keeping with this notion, mice lacking PAPP-A exhibit reduced body size, despite having normal circulating IGF-I concentrations. In contrast, human findings indicate that altered PAPP-A2 activity changes circulating IGF-I concentrations, although PAPP-A2 is also present in high concentrations in tissues. Thus, PAPP-A2 appears to impact circulating, as well as tissue, IGF-I activity. The enzymatic activity of PAPP-A and PAPP-A2 was recently discovered to be regulated by the protein Stanniocalcin-2 (STC2). By binding to the enzymatic sites of PAPP-A and PAPP-A2, STC2 inhibits their activity. To date, the majority of findings demonstrating the ability of pappalysins and STC2 to regulate IGF-I action are from preclinical studies. However, clinical studies are now beginning to emerge. In this review, we will summarize our data on STC2, PAPP-A and PAPP-A2 in humans. These results indicate that pappalysins and STC2 constitute an important IGF-I activity-regulating system that warrants further investigation.

First High-Density Linkage Map and QTL Fine Mapping for Growth-Related Traits of Spotted Sea bass (Lateolabrax maculatus)

Possessing powerful adaptive capacity and a pleasant taste, spotted sea bass (Lateolabrax maculatus) has a broad natural distribution and is one of the most popular mariculture fish in China. However, the genetic improvement program for this fish is still in its infancy. Growth is the most economically important trait and is controlled by quantitative trait loci (QTL); thus, the identification of QTLs and genetic markers for growth-related traits is an essential step for the establishment of marker-assisted selection (MAS) breeding programs. In this study, we report the first high-density linkage map of spotted sea bass constructed by sequencing 333 F1 generation individuals in a full-sib family using 2b-RAD technology. A total of 6883 SNP markers were anchored onto 24 linkage groups, spanning 2189.96 cM with an average marker interval of 0.33 cM. Twenty-four growth-related QTLs, including 13 QTLs for body weight and 11 QTLs for body length, were successfully detected, with phenotypic variance explained (PVE) ranging from 5.1 to 8.6%. Thirty potential candidate growth-related genes surrounding the associated SNPs were involved in cell adhesion, cell proliferation, cytoskeleton reorganization, calcium channels, and neuromodulation. Notably, the fgfr4 gene was detected in the most significant QTL; this gene plays a pivotal role in myogenesis and bone growth. The results of this study may facilitate marker-assisted selection for breeding populations and establish the foundation for further genomic and genetic studies investigating spotted sea bass.

Food intake-related genes in chicken determined through combinatorial genome-wide association study and transcriptome analysis

The chicken gizzard is the primary digestive and absorptive organ regulating food intake and metabolism. Body weight is a typical complex trait regulated by an interactive polygene network which is under the control of an interacting network of polygenes. To simplify these genotype-phenotype associations, the gizzard is a suitable target organ to preliminarily explore the mechanism underlying the regulation of chicken growth through controlled food intake. This study aimed to identify key food intake-related genes through combinatorial GWAS and transcriptome analysis. We performed GWAS of body weight in an F₂ intercrossed population and transcriptional profiling analysis of gizzards from chickens with different body weight. We identified a major 10 Mb quantitative trait locus (QTL) on chromosome 1 and numerous minor QTL distributed among 24 chromosomes. Combining data regarding QTL and gizzard gene expression, two hub genes, MLNR and HTR2A, and a list of core genes with small effect were found to be associated with food intake. Furthermore, the neuroactive ligand-receptor interaction pathway was found to play a key role in regulating the appetite of chickens. The present results show the major-minor gene interactions in metabolic pathways and provide insights into the genetic architecture and gene regulation during food intake in chickens.

Statistical Methods in Genome-Wide Association Studies

Since the initial success of genome-wide association studies (GWAS) in 2005, tens of thousands of genetic variants have been identified for hundreds of human diseases and traits. In a GWAS, genotype information at up to millions of genetic markers is collected from up to hundreds of thousands of individuals, together with their phenotype information. Several scientific goals can be accomplished through the analysis of GWAS data, including the identification of variants, genes, and pathways associated with diseases and traits of interest; the inference of the genetic architecture of these traits; and the development of genetic risk prediction models. In this review, we provide an overview of the statistical challenges in achieving these goals and recent progress in statistical methodology to address these challenges.

Comparative population genomic analysis uncovers novel genomic footprints and genes associated with small body size in Chinese pony

Background

Body size is considered as one of the most fundamental properties of an organism. Due to intensive breeding and artificial selection throughout the domestication history, horses exhibit striking variations for heights at withers and body sizes. Debao pony (DBP), a famous Chinese horse, is known for its small body size and lives in Guangxi mountains of southern China. In this study, we employed comparative population genomics to study the genetic basis underlying the small body size of DBP breed based on the whole genome sequencing data. To detect genomic signatures of positive selection, we applied three methods based on population comparison, fixation index (F_ST), cross population composite likelihood ratio (XP-CLR) and nucleotide diversity (θπ), and further analyzed the results to find genomic regions under selection for body size-related traits.

Results

A number of protein-coding genes in windows with the top 1% values of F_ST (367 genes), XP-CLR (681 genes), and log₂ (θπ ratio) (332 genes) were identified. The most significant signal of positive selection was mapped to the NELL1 gene, probably underlies the body size and development traits, and may also have been selected for short stature in the DBP population. In addition, some other loci on different chromosomes were identified to be potentially involved in the development of body size.

Conclusions

Results of our study identified some positively selected genes across the horse genome, which are possibly involved in body size traits. These novel candidate genes may be useful targets for clarifying our understanding of the molecular basis of body size and as such they should be of great interest for future research into the genetic architecture of relevant traits in horse breeding program.

A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model

BACKGROUND

The etiology of breast cancer is a complex system of interacting factors from multiple domains. New knowledge about breast cancer etiology continues to be produced by the research community, and the communication of this knowledge to other researchers, practitioners, decision makers, and the public is a challenge.

METHODS

We updated the previously published Paradigm model (PMID: 25017248) to create a framework that describes breast cancer etiology in four overlapping domains of biologic, behavioral, environmental, and social determinants. This new Paradigm II conceptual model was part of a larger modeling effort that included input from multiple experts in fields from genetics to sociology, taking a team and transdisciplinary approach to the common problem of describing breast cancer etiology for the population of California women in 2010. Recent literature was reviewed with an emphasis on systematic reviews when available and larger epidemiologic studies when they were not. Environmental chemicals with strong animal data on etiology were also included.

RESULTS

The resulting model illustrates factors with their strength of association and the quality of the available data. The published evidence supporting each relationship is made available herein, and also in an online dynamic model that allows for manipulation of individual factors leading to breast cancer (https://cbcrp.org/causes/).

CONCLUSIONS

The Paradigm II model illustrates known etiologic factors in breast cancer, as well as gaps in knowledge and areas where better quality data are needed.

IMPACT

The Paradigm II model can be a stimulus for further research and for better understanding of breast cancer etiology.

A genome-wide scan for pleiotropy between bone mineral density and nonbone phenotypes

Osteoporosis is the most common metabolic bone disorder globally and is characterized by skeletal fragility and microarchitectural deterioration. Genetic pleiotropy occurs when a single genetic element is associated with more than one phenotype. We aimed to identify pleiotropic loci associated with bone mineral density (BMD) and nonbone phenotypes in genome-wide association studies. In the discovery stage, the NHGRI-EBI Catalog was searched for genome-wide significant associations (P value < 5 × 10-8), excluding bone-related phenotypes. SNiPA was used to identify proxies of the significantly associated single nucleotide polymorphisms (SNPs) (r 2 = 1). We then assessed putative genetic associations of this set of SNPs with femoral neck (FN) and lumbar spine (LS) BMD data from the GEFOS Consortium. Pleiotropic variants were claimed at a false discovery rate < 1.4 × 10-3 for FN-BMD and < 1.5 × 10-3 for LS-BMD. Replication of these genetic markers was performed among more than 400 000 UK Biobank participants of European ancestry with available genetic and heel bone ultrasound data. In the discovery stage, 72 BMD-related pleiotropic SNPs were identified, and 12 SNPs located in 11 loci on 8 chromosomes were replicated in the UK Biobank. These SNPs were associated, in addition to BMD, with 14 different phenotypes. Most pleiotropic associations were exhibited by rs479844 (AP5B1, OVOL1 genes), which was associated with dermatological and allergic diseases, and rs4072037 (MUC1 gene), which was associated with magnesium levels and gastroenterological cancer. In conclusion, 12 BMD-related genome-wide significant SNPs showed pleiotropy with nonbone phenotypes. Pleiotropic associations can deepen the genetic understanding of bone-related diseases by identifying shared biological mechanisms with other diseases or traits.

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

SLIT3 deficiency attenuates pressure overload-induced cardiac fibrosis and remodeling

In pulmonary hypertension and certain forms of congenital heart disease, ventricular pressure overload manifests at birth and is an obligate hemodynamic abnormality that stimulates myocardial fibrosis, which leads to ventricular dysfunction and poor clinical outcomes. Thus, an attractive strategy is to attenuate the myocardial fibrosis to help preserve ventricular function. Here, by analyzing RNA-sequencing databases and comparing the transcript and protein levels of fibrillar collagen in WT and global-knockout mice, we found that slit guidance ligand 3 (SLIT3) was present predominantly in fibrillar collagen-producing cells and that SLIT3 deficiency attenuated collagen production in the heart and other nonneuronal tissues. We then performed transverse aortic constriction or pulmonary artery banding to induce left and right ventricular pressure overload, respectively, in WT and knockout mice. We discovered that SLIT3 deficiency abrogated fibrotic and hypertrophic changes and promoted long-term ventricular function and overall survival in both left and right ventricular pressure overload. Furthermore, we found that SLIT3 stimulated fibroblast activity and fibrillar collagen production, which coincided with the transcription and nuclear localization of the mechanotransducer yes-associated protein 1. These results indicate that SLIT3 is important for regulating fibroblast activity and fibrillar collagen synthesis in an autocrine manner, making it a potential therapeutic target for fibrotic diseases, especially myocardial fibrosis and adverse remodeling induced by persistent afterload elevation.

Whole genome sequence analysis reveals genetic structure and X-chromosome haplotype structure in indigenous Chinese pigs

Chinese indigenous pigs exhibit considerable phenotypic diversity, but their population structure and the genetic basis of agriculturally important traits need further exploration. Here, we sequenced the whole genomes of 24 individual pigs representing 22 breeds distributed throughout China. For comparison with European and commercial breeds (one pig per breed), we included seven published pig genomes with our new genomes for analyses. Our results showed that breeds grouped together based on morphological classifications are not necessarily more genetically similar to each other than to breeds from other groups. We found that genetic material from European pigs likely introgressed into five Chinese breeds. We have identified two new subpopulations of domestic pigs that encompass morphology-based criteria in China. The Southern Chinese subpopulation comprises the classical South Chinese Type and part of the Central China Type. In contrast, the Northern Chinese subpopulation comprises the North China Type, the Lower Yangtze River Basin Type, the Southwest Type, the Plateau Type, and the remainder of the Central China Type. Eight haplotypes and two recombination sites were identified within a conserved 40.09 Mb linkage-disequilibrium (LD) block on the X chromosome. Potential candidate genes (LEPR, FANCC, COL1A1, and PCCA) influencing body size were identified. Our findings provide insights into the phylogeny of Chinese indigenous pig breeds and benefit gene mining efforts to improve major economic traits.

Genetic Diversity and Signatures of Selection in a Native Italian Horse Breed Based on SNP Data

Simple Summary

The Bardigiano horse is a native Italian breed bred for living in rural areas, traditionally used in agriculture. The breed counts about 3000 horses, and it is nowadays mainly used for recreational purposes. The relatively small size and the closed status of the breed raise the issue of monitoring genetic diversity. We therefore characterized the breed’s genetic diversity based on molecular data. We showed a critical reduction of genetic variability mainly driven by past bottlenecks. We also highlighted homozygous genomic regions that might be the outcome of directional selection in recent years, in line with the conversion of Bardigiano horses from agricultural to riding purposes.

Abstract

Horses are nowadays mainly used for sport and leisure activities, and several local breeds, traditionally used in agriculture, have been exposed to a dramatic loss in population size and genetic diversity. The loss of genetic diversity negatively impacts individual fitness and reduces the potential long-term survivability of a breed. Recent advances in molecular biology and bioinformatics have allowed researchers to explore biodiversity one step further. This study aimed to evaluate the loss of genetic variability and identify genomic regions under selection pressure in the Bardigiano breed based on GGP Equine70k SNP data. The effective population size based on Linkage Disequilibrium (N_e) was equal to 39 horses, and it showed a decline over time. The average inbreeding based on runs of homozygosity (ROH) was equal to 0.17 (SD = 0.03). The majority of the ROH were relatively short (91% were ≤2 Mbp long), highlighting the occurrence of older inbreeding, rather than a more recent occurrence. A total of eight ROH islands, shared among more than 70% of the Bardigiano horses, were found. Four of them mapped to known quantitative trait loci related to morphological traits (e.g., body size and coat color) and disease susceptibility. This study provided the first genome-wide scan of genetic diversity and selection signatures in an Italian native horse breed.

Genetic Architecture Associated With Familial Short Stature

CONTEXT

Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known.

OBJECTIVE

To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction.

DESIGN AND SETTING

The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan.

PATIENTS AND INTERVENTIONS

The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method.

MAIN OUTCOME MEASURES

Genetic profile, polygenic risk predisposition score for risk prediction.

RESULTS

Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population.

CONCLUSION

A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.

The importance of including ethnically diverse populations in studies of quantitative trait evolution

For many traits, human variation is less a matter of categorical differences than quantitative variation, such as height, where individuals fall along a continuum from short to tall. Most recent studies utilize large population-based samples with whole-genome sequences to study the evolution of these traits and have made significant progress implementing a broad spectrum of techniques. However, relatively few studies of quantitative trait evolution include ethnically diverse populations, which often harbor the highest levels of genetic and phenotypic diversity. Thus, our ability to draw inferences about quantitative trait adaptation has been limited. Here, we review recent studies examining human quantitative trait adaptation, and argue that including ethnically diverse populations, particularly from Africa, will be especially informative for our understanding of how humans adapt to the world around them.

Review of Secondary Causes of Osteoporotic Fractures Due to Diabetes and Spinal Cord Injury

PURPOSE OF REVIEW

The aim of this review is to gain a better understanding of osteoporotic fractures and the different mechanisms that are driven in the scenarios of bone disuse due to spinal cord injury and osteometabolic disorders due to diabetes.

RECENT FINDINGS

Despite major advances in understanding the pathogenesis, prevention, and treatment of osteoporosis, the high incidence of impaired fracture healing remains an important complication of bone loss, leading to marked impairment of the health of an individual and economic burden to the medical system. This review underlines several pathways leading to bone loss and increased risk for fractures. Specifically, we addressed the different mechanisms leading to bone loss after a spinal cord injury and diabetes. Finally, it also encompasses the changes responsible for impaired bone repair in these scenarios, which may be of great interest for future studies on therapeutic approaches to treat osteoporosis and osteoporotic fractures.

The MUC6/AP2A2 Locus and Its Relevance to Alzheimer's Disease: A Review

We recently reported evidence of Alzheimer's disease (AD)-linked genetic variation within the mucin 6 (MUC6) gene on chromosome 11p, nearby the adaptor-related protein complex 2 subunit alpha 2 (AP2A2) gene. This locus has interesting features related to human genomics and clinical research. MUC6 gene variants have been reported to potentially influence viral-including herpesvirus-immunity and the gut microbiome. Within the MUC6 gene is a unique variable number of tandem repeat (VNTR) region. We discovered an association between MUC6 VNTR repeat expansion and AD pathologic severity, particularly tau proteinopathy. Here, we review the relevant literature. The AD-linked VNTR polymorphism may also influence AP2A2 gene expression. AP2A2 encodes a polypeptide component of the adaptor protein complex, AP-2, which is involved in clathrin-coated vesicle function and was previously implicated in AD pathogenesis. To provide background information, we describe some key knowledge gaps in AD genetics research. The "missing/hidden heritability problem" of AD is highlighted. Extensive portions of the human genome, including the MUC6 VNTR, have not been thoroughly evaluated due to limitations of existing high-throughput sequencing technology. We present and discuss additional data, along with cautionary considerations, relevant to the hypothesis that MUC6 repeat expansion influences AD pathogenesis.

Use of whole-genome sequence data and novel genomic selection strategies to improve selection for age at puberty in tropically-adapted beef heifers

Background

In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies; including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved.

Methods

Genotypes and phenotypes were obtained from two research herds. In total, 868 Brahman and 960 Tropical Composite heifers were recorded in the first population and 3695 Brahman, Santa Gertrudis and Droughtmaster heifers were recorded in the second population. Genotypes were imputed to 23 million whole-genome sequence variants. Eight strategies were used to pre-select variants from genome-wide association study (GWAS) results using conditional or joint (COJO) analyses. Pre-selected variants were included in three models, GBLUP with a single genomic relationship matrix (SGRM), GBLUP MGRM and BayesR. Five-way cross-validation was used to test the effect of marker panel density (6 K, 50 K and 800 K), analysis model, and inclusion of pre-selected WGS variants on prediction accuracy.

Results

In all tested scenarios, prediction accuracies for age at puberty were highest in BayesR analyses. The addition of pre-selected WGS variants had little effect on the accuracy of prediction when BayesR was used. The inclusion of WGS variants that were pre-selected using a meta-analysis with COJO analyses by chromosome, fitted in a MGRM model, had the highest prediction accuracies in the GBLUP analyses, regardless of marker density. When the low-density (6 K) panel was used, the prediction accuracy of GBLUP was equal (0.42) to that with the high-density panel when only six additional sequence variants (identified using meta-analysis COJO by chromosome) were included.

Conclusions

While BayesR consistently outperforms other methods in terms of prediction accuracies, reasonable improvements in accuracy can be achieved when using GBLUP and low-density panels with the inclusion of a relatively small number of highly relevant WGS variants.

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.

The SNP-Based Heritability - A Commentary on Yang et al. (2010)

I write this commentary as a part of a special issue published in this journal to celebrate Nick Martin's contribution to the field of human genetics. In this commentary, I briefly describe the background of the Yang et al. (2010) study and show some of the unpublished details of this study, its contribution to tackling the missing heritability problem and Nick's contribution to the work.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

Genetic and environmental influences on human height from infancy through adulthood at different levels of parental education

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

Growth hormone receptor promotes breast cancer progression via the BRAF/MEK/ERK signaling pathway

Growth hormone receptor (GHR), a member of the class I cytokine receptor family, plays key roles in cancer progression. Recently, GHR has been reported to be associated with breast cancer development, but the molecular mechanism of GHR in this malignancy is not fully understood. To investigate this issue, we stably inhibited GHR in breast cancer cell lines, which were observed to reduce cell proliferation, tumor growth and induction of apoptosis, and arrest the cell‐cycle arrest at the G1–S phase transition. In addition, GHR silencing suppressed the protein levels of B‐Raf proto‐oncogene, serine/threonine kinase (BRAF), Mitogen‐activated protein kinase kinase (MEK) and Extracellular regulated protein kinases (ERK). These findings suggest that GHR may mediate breast cell progression and apoptosis through control of the cell cycle via the BRAF/MEK/ERK signaling pathway.

Adult body height and age-related macular degeneration in healthy individuals: A nationwide population-based survey from Korea

We sought to evaluate the relationship between adult body height and risk of age-related macular degeneration (AMD) among healthy Koreans using nationwide population-based data. We analyzed data derived from the Korea National Health and Nutrition Examination Survey 2008–2011. Participants over 40 years of age were included in the sample after excluding individuals with systemic comorbidities or missing relevant data. The presence and severity of AMD were graded using fundus photographs. The relationship between body height and risk of AMD was determined using multiple logistic regression analyses. Among a total of 8,435 participants, 544 (6.45%) had AMD: 502 (5.95%) with early AMD and 42 (0.5%) with late AMD. In multivariate-adjusted analyses, taller body height was significantly associated with a lower prevalence of AMD (odds ratio [OR], 0.89; 95% confidence interval [CI], 0.81–0.99), while body mass index (BMI) was not associated with AMD. An inverse association between body height and risk of AMD was observed most frequently in participants under 65 years of age (OR, 0.81; 95% CI, 0.70–0.94). Furthermore, body height showed an inverse association with risk of AMD among obese participants (BMI ≥25.0 kg/m²) (OR, 0.75; 95% CI, 0.60–0.93). Subgroup analysis by AMD type disclosed a significant inverse association between body height and early AMD (OR, 0.87; 95% CI, 0.79–0.97) but not late AMD. Our results suggest that shorter body height is independently associated with increased risk of AMD, especially early AMD, in a dose-response manner in people who are obese or under 65 years of age.

The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication

The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.

Genetic Variation in Steroid and Xenobiotic Metabolizing Pathways and Enterolactone Excretion Before and After Flaxseed Intervention in African American and European American Women

BACKGROUND

Metabolism and excretion of the phytoestrogen enterolactone (ENL), which has been associated with breast cancer risk, may be affected by variation in steroid hormone and xenobiotic-metabolizing genes.

METHODS

We conducted a randomized, crossover flaxseed intervention study in 252 healthy, postmenopausal women [137 European ancestry (EA) and 115 African ancestry (AA)] from western New York. Participants were randomly assigned to maintain usual diet or consume 10 g/day ground flaxseed for 6 weeks. After a 2-month washout period, participants crossed over to the other diet condition for an additional 6 weeks. Urinary ENL excretion was measured by gas chromatography-mass spectrometry and 70 polymorphisms in 29 genes related to steroid hormone and xenobiotic metabolism were genotyped. Mixed additive genetic models were constructed to examine association of genetic variation with urinary ENL excretion at baseline and after the flaxseed intervention.

RESULTS

SNPs in several genes were nominally (P < 0.05) associated with ENL excretion at baseline and/or after intervention: ESR1, CYP1B1, COMT, CYP3A5, ARPC1A, BCL2L11, SHBG, SLCO1B1, and ZKSCAN5. A greater number of SNPs were associated among AA women than among EA women, and no SNPs were associated in both races. No SNP-ENL associations were statistically significant after correction for multiple comparisons.

CONCLUSIONS

Variation in several genes related to steroid hormone metabolism was associated with lignan excretion at baseline and/or after flaxseed intervention among postmenopausal women.

IMPACT

These findings may contribute to our understanding of the differences observed in urinary ENL excretion among AA and EA women and thus hormone-related breast cancer risk.

What is creating the height premium? New evidence from a Mendelian randomization analysis in China

This study uses a Mendelian randomization approach to resolve the difficulties of identifying the causal relationship between height and earnings by using a unique sample of 3,427 respondents from mainland China with sociodemographic information linked to individual genotyping data. Exploiting genetic variations to create instrumental variables for observed height, we find that while OLS regressions yield that an additional centimeter in height is associated with a 10-13% increase in one's annual earnings, IV estimates reveal only an insubstantial causal effect of height. Further analyses suggest that the observed height premium is likely to pick up the impacts of several cognitive/noncognitive skills on earnings confounded in previous studies, such as mental health, risk preference, and personality factors. Our study is the first empirical study that employs genetic IVs in developing countries, and our results contribute to the recent debate on the mechanism of height premium.

A High-Quality Genome Assembly of the North American Song Sparrow, Melospiza melodia

The song sparrow, Melospiza melodia, is one of the most widely distributed species of songbirds found in North America. It has been used in a wide range of behavioral and ecological studies. This species' pronounced morphological and behavioral diversity across populations makes it a favorable candidate in several areas of biomedical research. We have generated a high-quality de novo genome assembly of M. melodia using Illumina short read sequences from genomic and in vitro proximity-ligation libraries. The assembled genome is 978.3 Mb, with a physical coverage of 24.9×, N50 scaffold size of 5.6 Mb and N50 contig size of 31.7 Kb. Our genome assembly is highly complete, with 87.5% full-length genes present out of a set of 4,915 universal single-copy orthologs present in most avian genomes. We annotated our genome assembly and constructed 15,086 gene models, a majority of which have high homology to related birds, Taeniopygia guttata and Junco hyemalis In total, 83% of the annotated genes are assigned with putative functions. Furthermore, only ∼7% of the genome is found to be repetitive; these regions and other non-coding functional regions are also identified. The high-quality M. melodia genome assembly and annotations we report will serve as a valuable resource for facilitating studies on genome structure and evolution that can contribute to biomedical research and serve as a reference in population genomic and comparative genomic studies of closely related species.

Genotyping Array Design and Data Quality Control in the Million Veteran Program

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other 'omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP's substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Revisiting the Population Genetics of Human Height

CONTEXT

Recent advances in genetics and genomics present unique opportunities for enhancing knowledge of human physiology and disease susceptibility. An outstanding example of these new insights may be seen in the study of human height, of which it has been estimated that approximately 80% is genetically determined. Over the past decade, large-scale population analyses have led to the identification of novel variation in genes and loci individually associated with changes in adult height of as much as 2 cm.

OBJECTIVE

To assess these same variants in the genomes of 213 158 individuals compiled by the Genome Aggregation Database (GnomAD) consortium, representing different population groups from around the world.

RESULTS

The majority of these height-changing alleles are substantially less prevalent in GnomAD than found previously in other cohorts, with 4 of 5 amino acid substitution variants with the largest impact on adult height being more frequent in the European population than in other groups.

CONCLUSIONS

A larger-scale analysis of individuals from diverse backgrounds will be necessary to ensure a full and accurate understanding of the genetic underpinnings of human height throughout the world, and additional studies will be needed to discern the biochemical and molecular mechanisms governing the physiological processes that explain how these variant proteins might selectively impact the biology of the growth plate. Broader understanding of the genetics of height also should set the stage for more comprehensive investigation into the causes of prevalent polygenic human diseases.

Characterisation of genetic regulatory effects for osteoporosis risk variants in human osteoclasts

Background

Osteoporosis is a complex disease with a strong genetic contribution. A recently published genome-wide association study (GWAS) for estimated bone mineral density (eBMD) identified 1103 independent genome-wide significant association signals. Most of these variants are non-coding, suggesting that regulatory effects may drive many of the associations. To identify genes with a role in osteoporosis, we integrate the eBMD GWAS association results with those from our previous osteoclast expression quantitative trait locus (eQTL) dataset.

Results

We identify sixty-nine significant cis-eQTL effects for eBMD GWAS variants after correction for multiple testing. We detect co-localisation of eBMD GWAS and osteoclast eQTL association signals for 21 of the 69 loci, implicating a number of genes including CCR5, ZBTB38, CPE, GNA12, RIPK3, IQGAP1 and FLCN. Summary-data-based Mendelian Randomisation analysis of the eBMD GWAS and osteoclast eQTL datasets identifies significant associations for 53 genes, with TULP4 presenting as a strong candidate for pleiotropic effects on eBMD and gene expression in osteoclasts. By performing analysis using the GARFIELD software, we demonstrate significant enrichment of osteoporosis risk variants among high-confidence osteoclast eQTL across multiple GWAS P value thresholds. Mice lacking one of the genes of interest, the apoptosis/necroptosis gene RIPK3, show disturbed bone micro-architecture and increased osteoclast number, highlighting a new biological pathway relevant to osteoporosis.

Conclusion

We utilise a unique osteoclast eQTL dataset to identify a number of potential effector genes for osteoporosis risk variants, which will help focus functional studies in this area.

Comprehensive Analysis of the Genetic and Epigenetic Mechanisms of Osteoporosis and Bone Mineral Density

Osteoporosis is a skeletal disorder characterized by a systemic impairment of bone mineral density (BMD). Genome-wide association studies (GWAS) have identified hundreds of susceptibility loci for osteoporosis and BMD. However, the vast majority of susceptibility loci are located in non-coding regions of the genome and provide limited information about the genetic mechanisms of osteoporosis. Herein we performed a comprehensive functional analysis to investigate the genetic and epigenetic mechanisms of osteoporosis and BMD. BMD and osteoporosis are found to share many common susceptibility loci, and the corresponding susceptibility genes are significantly enriched in bone-related biological pathways. The regulatory element enrichment analysis indicated that BMD and osteoporosis susceptibility loci are significantly enriched in 5′UTR and DNase I hypersensitive sites (DHSs) of peripheral blood immune cells. By integrating GWAS and expression Quantitative Trait Locus (eQTL) data, we found that 15 protein-coding genes are regulated by the osteoporosis and BMD susceptibility loci. Our analysis provides new clues for a better understanding of the pathogenic mechanisms and offers potential therapeutic targets for osteoporosis.