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

Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error

Corneal curvature, a highly heritable trait, is a key clinical endophenotype for myopia - a major cause of visual impairment and blindness in the world. Here we present a trans-ethnic meta-analysis of corneal curvature GWAS in 44,042 individuals of Caucasian and Asian with replication in 88,218 UK Biobank data. We identified 47 loci (of which 26 are novel), with population-specific signals as well as shared signals across ethnicities. Some identified variants showed precise scaling in corneal curvature and eye elongation (i.e. axial length) to maintain eyes in emmetropia (i.e. HDAC11/FBLN2 rs2630445, RBP3 rs11204213); others exhibited association with myopia with little pleiotropic effects on eye elongation. Implicated genes are involved in extracellular matrix organization, developmental process for body and eye, connective tissue cartilage and glycosylation protein activities. Our study provides insights into population-specific novel genes for corneal curvature, and their pleiotropic effect in regulating eye size or conferring susceptibility to myopia.

Genome-wide association identifies seven loci for pelvic organ prolapse in Iceland and the UK Biobank

Pelvic organ prolapse (POP) is a downward descent of one or more of the pelvic organs, resulting in a protrusion of the vaginal wall and/or uterus. We performed a genome-wide association study of POP using data from Iceland and the UK Biobank, a total of 15,010 cases with hospital-based diagnosis code and 340,734 female controls, and found eight sequence variants at seven loci associating with POP (P < 5 × 10-8); seven common (minor allele frequency >5%) and one with minor allele frequency of 4.87%. Some of the variants associating with POP also associated with traits of similar pathophysiology. Of these, rs3820282, which may alter the estrogen-based regulation of WNT4, also associates with leiomyoma of uterus, gestational duration and endometriosis. Rs3791675 at EFEMP1, a gene involved in connective tissue homeostasis, also associates with hernias and carpal tunnel syndrome. Our results highlight the role of connective tissue metabolism and estrogen exposure in the etiology of POP.

Environmental temperature and growth faltering in African children: a cross-sectional study

BACKGROUND

Child growth faltering persists in sub-Saharan Africa despite the scale-up of nutrition, water, and sanitation interventions over the past 2 decades. High temperatures have been hypothesised to contribute to child growth faltering via an adaptive response to heat, reduced appetite, and the energetic cost of thermoregulation. We did a cross-sectional study to assess whether child growth faltering is related to environmental temperature in sub-Saharan Africa.

METHODS

Data were extracted from 52 Demographic and Heath Surveys, dating from 2003 to 2016, that recorded anthropometric data in children aged 0-5 years, and were linked with remotely sensed monthly mean daytime land surface temperature for 2000-16. The odds of stunting (low height-for-age), wasting (low weight-for-height), and underweight (low weight-for-age) relative to monthly mean daytime land surface temperature were determined using multivariable logistic regression.

FINDINGS

The study population comprised 656 107 children resident in 373 012 households. Monthly mean daytime land surface temperature above 35°C was associated with increases in the odds of wasting (odds ratio 1·27, 95% CI 1·16-1·38; p<0·0001), underweight (1·09, 1·02-1·16; p=0·0073), and concurrent stunting with wasting (1·23, 1·07-1·41; p=0·0037), but a reduction in stunting (0·90, 0·85-0·96; p=0·00047) compared with a monthly mean daytime land surface temperature of less than 30°C.

INTERPRETATION

Children living in hotter parts of sub-Saharan Africa are more likely to be wasted, underweight, and concurrently stunted and wasted, but less likely to be stunted, than in cooler areas. Studies are needed to further investigate the relationship between temperature and child growth, including whether there is a direct effect not mediated by food security, regional wealth, and other environmental variables. Rising temperature, linked to anthropogenic climate change, might increase child growth faltering in sub-Saharan Africa.

FUNDING

UK Medical Research Council and UK Global Challenges Research Fund.

Genome-wide, integrative analysis of circular RNA dysregulation and the corresponding circular RNA-microRNA-mRNA regulatory axes in autism

Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank

Although snoring is common in the general population, its aetiology has been largely understudied. Here we report a genetic study on snoring (n ~ 408,000; snorers ~ 152,000) using data from the UK Biobank. We identify 42 genome-wide significant loci, with an SNP-based heritability estimate of ~10% on the liability scale. Genetic correlations with body mass index, alcohol intake, smoking, schizophrenia, anorexia nervosa and neuroticism are observed. Gene-based associations identify 173 genes, including DLEU7, MSRB3 and POC5, highlighting genes expressed in the brain, cerebellum, lungs, blood and oesophagus. We use polygenic scores (PGS) to predict recent snoring and probable obstructive sleep apnoea (OSA) in an independent Australian sample (n ~ 8000). Mendelian randomization analyses suggest a potential causal relationship between high BMI and snoring. Altogether, our results uncover insights into the aetiology of snoring as a complex sleep-related trait and its role in health and disease beyond it being a cardinal symptom of OSA.

Snoring is common in the population and tends to be more prevalent in older and/or male individuals. Here, the authors perform GWAS for habitual snoring, identify 41 genomic loci and explore potential causal relationships with anthropometric and cardiometabolic disease traits.

Body height in young adult men and risk of dementia later in adult life

This study examined the relationship between body height and dementia and explored the impact of intelligence level, educational attainment, early life environment and familial factors. A total of 666,333 men, 70,608 brothers, and 7388 twin brothers born 1939-1959 and examined at the conscript board were followed in Danish nationwide registers (1969-2016). Cox regression models were applied to analyze the association between body height and dementia. Within-brothers and within-twin pair analyses were conducted to explore the role of shared familial factors including partly shared genetics. In total, 10,599 men were diagnosed with dementia. The association between one z-score difference in body height and dementia (HR: 0.90, 95% CI: 0.89;0.90) was inverse and weakened slightly after adjustment for intelligence test scores and educational level. The associations persisted in within-brother analysis and revealed a stronger, but less precise, point estimate than the cohort analysis of brothers. The twin analysis showed similar, but imprecise estimates.

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.

Identification of 34 genes conferring genetic and pharmacological risk for the comorbidity of schizophrenia and smoking behaviors

The prevalence of smoking is significantly higher in persons with schizophrenia (SCZ) than in the general population. However, the biological mechanisms of the comorbidity of smoking and SCZ are largely unknown. This study aimed to reveal shared biological pathways for the two diseases by analyzing data from two genome-wide association studies with a total sample size of 153,898. With pathway-based analysis, we first discovered 18 significantly enriched pathways shared by SCZ and smoking, which were classified into five groups: postsynaptic density, cadherin binding, dendritic spine, long-term depression, and axon guidance. Then, by using an integrative analysis of genetic, epigenetic, and expression data, we found not only 34 critical genes (e.g., PRKCZ, ARHGEF3, and CDKN1A) but also various risk-associated SNPs in these genes, which convey susceptibility to the comorbidity of the two disorders. Finally, using both in vivo and in vitro data, we demonstrated that the expression profiles of the 34 genes were significantly altered by multiple psychotropic drugs. Together, this multi-omics study not only reveals target genes for new drugs to treat SCZ but also reveals new insights into the shared genetic vulnerabilities of SCZ and smoking behaviors.

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.

Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies

Genetic risk prediction is an important problem in human genetics, and accurate prediction can facilitate disease prevention and treatment. Calculating polygenic risk score (PRS) has become widely used due to its simplicity and effectiveness, where only summary statistics from genome-wide association studies are needed in the standard method. Recently, several methods have been proposed to improve standard PRS by utilizing external information, such as linkage disequilibrium and functional annotations. In this paper, we introduce EB-PRS, a novel method that leverages information for effect sizes across all the markers to improve prediction accuracy. Compared to most existing genetic risk prediction methods, our method does not need to tune parameters nor external information. Real data applications on six diseases, including asthma, breast cancer, celiac disease, Crohn's disease, Parkinson's disease and type 2 diabetes show that EB-PRS achieved 307.1%, 42.8%, 25.5%, 3.1%, 74.3% and 49.6% relative improvements in terms of predictive r2 over standard PRS method with optimally tuned parameters. Besides, compared to LDpred that makes use of LD information, EB-PRS also achieved 37.9%, 33.6%, 8.6%, 36.2%, 40.6% and 10.8% relative improvements. We note that our method is not the first method leveraging effect size distributions. Here we first justify our method by presenting theoretical optimal property over existing methods in this class of methods, and substantiate our theoretical result with extensive simulation results. The R-package EBPRS that implements our method is available on CRAN.

Pathogenic/likely pathogenic variants in the SHOX, GHR and IGFALS genes among Indian children with idiopathic short stature

Background Our objective was to estimate the prevalence of pathogenic/likely pathogenic variants in the SHOX, GHR, and IGFALS genes among Indian children with idiopathic short stature (ISS), and assess the genotype-phenotype correlation. Methods We recruited 61 children with short stature, who were born appropriate for gestational age, had no obvious dysmorphism or disproportion, and in whom step-wise investigative work-up (including provocative growth hormone test) was normal. Multiplex ligation-dependent probe amplification was undertaken for identifying deletions/duplications in the SHOX gene. Bidirectional sequencing was performed for identifying variants in the SHOX and GHR genes in all, and for the IGFALS gene in those with serum insulin-like growth factor-1 (IGF-1) <-1 standard deviation. The genotype-phenotype correlation was studied. Results Four children (6.5%) had pathogenic heterozygous variants in the SHOX gene, with one child each having duplication of exon 5, splice site point variant c.278-1G > C in exon 3, partial deletion and complete deletion. None of the patients had pathogenic variants in the GHR gene. Of the 39 patients in whom the IGFALS gene was sequenced, novel heterozygous likely pathogenic variants were found in two children. One had the frameshift variant c.764_765insT, p.A265Gfs*114. The second had the missense variant c.1793G > A, p.R598H predicted by MutationTaster as 'disease causing', and indicated by the protein-modelling study as having compromised binding with IGF-1 and insulin-like growth factor binding protein-3 (IGFBP-3) due to altered conformation of the interacting loop. Conclusions Pathogenic variants in the SHOX and IGFALS genes account for a significant proportion of Indian children with ISS. Further molecular studies using next generation sequencing are needed to gain insight into pathophysiological mechanisms and effective treatment strategies for ISS.

Functional and population genetic features of copy number variations in two dairy cattle populations

BACKGROUND

Copy Number Variations (CNVs) are gain or loss of DNA segments that are known to play a role in shaping a wide range of phenotypes. In this study, we used two dairy cattle populations, Holstein Friesian and Jersey, to discover CNVs using the Illumina BovineHD Genotyping BeadChip aligned to the ARS-UCD1.2 assembly. The discovered CNVs were investigated for their functional impact and their population genetics features.

RESULTS

We discovered 14,272 autosomal CNVs, which were aggregated into 1755 CNV regions (CNVR) from 451 animals. These CNVRs together cover 2.8% of the bovine autosomes. The assessment of the functional impact of CNVRs showed that rare CNVRs (MAF < 0.01) are more likely to overlap with genes, than common CNVRs (MAF ≥ 0.05). The Population differentiation index (Fst) based on CNVRs revealed multiple highly diverged CNVRs between the two breeds. Some of these CNVRs overlapped with candidate genes such as MGAM and ADAMTS17 genes, which are related to starch digestion and body size, respectively. Lastly, linkage disequilibrium (LD) between CNVRs and BovineHD BeadChip SNPs was generally low, close to 0, although common deletions (MAF ≥ 0.05) showed slightly higher LD (r2 = ~ 0.1 at 10 kb distance) than the rest. Nevertheless, this LD is still lower than SNP-SNP LD (r2 = ~ 0.5 at 10 kb distance).

CONCLUSIONS

Our analyses showed that CNVRs detected using BovineHD BeadChip arrays are likely to be functional. This finding indicates that CNVs can potentially disrupt the function of genes and thus might alter phenotypes. Also, the population differentiation index revealed two candidate genes, MGAM and ADAMTS17, which hint at adaptive evolution between the two populations. Lastly, low CNVR-SNP LD implies that genetic variation from CNVs might not be fully captured in routine animal genetic evaluation, which relies solely on SNP markers.

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.

Influence of Genetic Interactions on Polygenic Prediction

Prediction of phenotypes from genotypes is an important objective to fulfill the promises of genomics, precision medicine and agriculture. Although it's now possible to account for the majority of genetic variation through model fitting, prediction of phenotypes remains a challenge, especially across populations that have diverged in the past. In this study, we designed simulation experiments to specifically investigate the role of genetic interactions in failure of polygenic prediction. We found that non-additive genetic interactions can significantly reduce the accuracy of polygenic prediction. Our study demonstrated the importance of considering genetic interactions in genetic prediction.

A brief history of human disease genetics

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.

Exploratory analysis of genetic variants influencing molecular traits in cerebral cortex of suicide completers

Genetic factors have been implicated in suicidal behavior. It has been suggested that one of the roles of genetic factors in suicide could be represented by the effect of genetic variants on gene expression regulation. Alteration in the expression of genes participating in multiple biological systems in the suicidal brain has been demonstrated, so it is imperative to identify genetic variants that could influence gene expression or its regulatory mechanisms. In this study, we integrated DNA methylation, gene expression, and genotype data from the prefrontal cortex of suicides to identify genetic variants that could be factors in the regulation of gene expression, generally called quantitative trait locus (xQTLs). We identify 6,224 methylation quantitative trait loci and 2,239 expression quantitative trait loci (eQTLs) in the prefrontal cortex of suicide completers. The xQTLs identified influence the expression of genes involved in neurodevelopment and cell organization. Two of the eQTLs identified (rs8065311 and rs1019238) were previously associated with cannabis dependence, highlighting a candidate genetic variant for the increased suicide risk in subjects with substance use disorders. Our findings suggest that genetic variants may regulate gene expression in the prefrontal cortex of suicides through the modulation of promoter and enhancer activity, and to a lesser extent, binding transcription factors.

Uncovering the complex genetics of human character

Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

MC4R Variant rs17782313 Associates With Increased Levels of DNAJC27, Ghrelin, and Visfatin and Correlates With Obesity and Hypertension in a Kuwaiti Cohort

Melanocortin 4 receptor (MC4R), a notable component of the melanocortin system, regulates appetite, body weight, and energy homeostasis. Genome-wide association studies have identified several MC4R variants associated with adiposity; of these, rs17782313, which is associated with increased body mass index (BMI) and overeating behavior, is of particular interest. Another gene associated with increased adiposity in global genome-wide association studies is DNAJC27, a heat shock protein known to be elevated in obesity. The detailed mechanisms underlying the role of MC4R variants in the biological pathways underlying metabolic disorders are not well-understood. To address this, we assessed variations of rs17782313 in a cohort of 282 Arab individuals from Kuwait, who are deeply phenotyped for anthropometric and metabolic traits and various biomarkers, including DNAJC27. Association tests showed that the rs17782313_C allele was associated with BMI and DNAJC27 levels. Increased levels of DNAJC27 reduced the MC4R-mediated formation of cAMP in MC4R ACTOne stable cells. In conclusion, this study demonstrated an association between the rs17782313 variant near MC4R and increased BMI and DNAJC27 levels and established a link between increased DNAJC27 levels and lower cAMP levels. We propose that regulation of MC4R activity by DNAJC27 enhances appetite through its effect on cAMP, thereby regulating obesity.

Evolutionary Strategies for Body Size

Humans show marked variation in body size around the world, both within and among populations. At present, the tallest people in the world are from the Netherlands and the Balkan countries, while the shortest populations are central African Pygmies. There are genetic, genetic plasticity, developmental, and environmental bases for size variation in Homo sapiens from the recent past and the present. Early populations of Homo species also have shown considerable size variation. Populations from the present and the past are also marked by sexual dimorphism, which, itself, shows group variation. There is abundant evidence for the effects of limited food and disease on human growth and resultant adult body size. This environmental influence has been reflected in "secular trends" (over a span of years) in growth and adult size from socioeconomic prosperity or poverty (availability of resources). Selective and evolutionary advantages of small or large body size also have been documented. Heritability for human height is relatively great with current genome-wide association studies (GWAS) identifying hundreds of genes leading to causes of growth and adult size variation. There are also endocrinological pathways limiting growth. An example is the reduced tissue sensitivity to human growth hormone (HGH) and insulin-like growth factor (IGF-1) in Philippine and African hunter-gatherer populations. In several short-statured hunter-gatherer populations (Asian, African, and South American), it has been hypothesized that short life expectancy has selected for early maturity and truncated growth to enhance fertility. Some island populations of humans and other mammals are thought to have been selected for small size because of limited resources, especially protein. The high-protein content of milk as a staple food may contribute to tall stature in East African pastoral peoples. These and other evolutionary questions linked to life history, male competition, reproduction, and mobility are explored in this paper.

Uncovering the complex genetics of human temperament

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

Genetic Polymorphisms Associated with Idiopathic Short Stature and First-Year Response to Growth Hormone Treatment

BACKGROUND/AIMS

The term idiopathic short stature (ISS) describes short stature of unknown, but likely polygenic, etiology. This study aimed to identify genetic polymorphisms associated with the ISS phenotype, and with growth response to supplemental GH.

METHODS

Using a case-control analysis we compared the prevalence of "tall" versus "short" alleles at 52 polymorphic loci (17 in growth-related candidate genes, 35 identified in prior genome-wide association studies of adult height) in 94 children with ISS followed in the Genetics and Neuroendocrinology of Short Stature International Study, versus 143 controls from the Fels Longitudinal Study.

RESULTS

Four variants were nominally associated with ISS using a genotypic model, confirmed by a simultaneous confident inference approach: compared with controls children with ISS had lower odds of "tall" alleles (odds ratio, 95% CI) for GHR (0.52, 0.29-0.96); rs2234693/ESR1 (0.50, 0.25-0.98); rs967417/BMP2 (0.39, 0.17-0.93), and rs4743034/ZNF462 (0.40, 0.18-0.89). Children with ISS also had lower odds of the "tall" allele (A) at the IGFBP3 -202 promoter polymorphism (rs2855744; 0.40, 0.20-0.80) in the simultaneous confident inference analysis. A significant association with 1st-year height SD score increase during GH treatment was observed with rs11205277, located near 4 known genes: MTMR11, SV2A, HIST2H2AA3, and SF3B4; the latter, in which heterozygous mutations occur in Nager acrofacial dysostosis, appears the most relevant gene.

CONCLUSIONS

In children with ISS we identified associations with "short" alleles at a number of height-related loci. In addition, a polymorphic variant located near SF3B4 was associated with the GH treatment response in our cohort. The findings in our small study warrant further investigation.

Benefits and limitations of genome-wide association studies

Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS.

LIN28B affects gene expression at the hypothalamic-pituitary axis and serum testosterone levels

Genome-wide association studies (GWAS) have recurrently associated sequence variation nearby LIN28B with pubertal timing, growth and disease. However, the biology linking LIN28B with these traits is still poorly understood. With our study, we sought to elucidate the mechanisms behind the LIN28B associations, with a special focus on studying LIN28B function at the hypothalamic-pituitary (HP) axis that is ultimately responsible for pubertal onset. Using CRISPR-Cas9 technology, we first generated lin28b knockout (KO) zebrafish. Compared to controls, the lin28b KO fish showed both accelerated growth tempo, reduced adult size and increased expression of mitochondrial genes during larval development. Importantly, data from the knockout zebrafish models and adult humans imply that LIN28B expression has potential to affect gene expression in the HP axis. Specifically, our results suggest that LIN28B expression correlates positively with the expression of ESR1 in the hypothalamus and POMC in the pituitary. Moreover, we show how the pubertal timing advancing allele (T) for rs7759938 at the LIN28B locus associates with higher testosterone levels in the UK Biobank data. Overall, we provide novel evidence that LIN28B contributes to the regulation of sex hormone pathways, which might help explain why the gene associates with several distinct traits.

Adamts17 is involved in skeletogenesis through modulation of BMP-Smad1/5/8 pathway

Fibrillin microfibrils are ubiquitous elements of extracellular matrix assemblies that play crucial roles in regulating the bioavailability of growth factors of the transforming growth factor beta superfamily. Recently, several "a disintegrin and metalloproteinase with thrombospondin motifs" (ADAMTS) proteins were shown to regulate fibrillin microfibril function. Among them, ADAMTS17 is the causative gene of Weill-Marchesani syndrome (WMS) and Weill-Marchesani-like syndrome, of which common symptoms are ectopia lentis and short stature. ADAMTS17 has also been linked to height variation in humans; however, the molecular mechanisms whereby ADAMTS17 regulates skeletal growth remain unknown. Here, we generated Adamts17-/- mice to examine the role of Adamts17 in skeletogenesis. Adamts17-/- mice recapitulated WMS, showing shorter long bones, brachydactyly, and thick skin. The hypertrophic zone of the growth plate in Adamts17-/- mice was shortened, with enhanced fibrillin-2 deposition, suggesting increased incorporation of fibrillin-2 into microfibrils. Comprehensive gene expression analysis of growth plates using laser microdissection and RNA sequencing indicated alteration of the bone morphogenetic protein (BMP) signaling pathway after Adamts17 knockout. Consistent with this, phospho-Smad1 levels were downregulated in the hypertrophic zone of the growth plate and in Adamts17-/- primary chondrocytes. Delayed terminal differentiation of Adamts17-/- chondrocytes, observed both in primary chondrocyte and primordial metatarsal cultures, and was prevented by BMP treatment. Our data indicated that Adamts17 is involved in skeletal formation by modulating BMP-Smad1/5/8 pathway, possibly through inhibiting the incorporation of fibrillin-2 into microfibrils. Our findings will contribute to further understanding of disease mechanisms and will facilitate the development of therapeutic interventions for WMS.

Bone morphogenetic protein 2 is a depot-specific regulator of human adipogenesis

BACKGROUND

Bone morphogenetic proteins (BMPs) regulate adipogenesis but it is not clear whether they influence regional adipose tissue (AT) development in humans.

OBJECTIVE

To characterise BMP2 expression, BMP2-SMAD1/5/8 signalling, and BMP2's potential effect on proliferation and adipogenesis in human subcutaneous abdominal and gluteal AT and its constituent preadipocytes.

METHODS

BMP2 expression was measured in whole AT and immortalised preadipocytes via qPCR and Western blot; secreted/circulating BMP2 was measured by ELISA. The effect of BMP2 on preadipocyte proliferation was evaluated using a fluorescent assay. BMP2's effect on adipogenesis in immortalised preadipocytes was determined via qPCR of adipogenic markers and cellular triacylglycerol (TAG) accumulation. BMP2-SMAD1/5/8 signalling was assessed in immortalised preadipocytes via Western blot and qPCR of ID1 expression.

RESULTS

BMP2 was expressed and released by abdominal and gluteal AT and preadipocytes. Exogenous BMP2 dose dependently promoted adipogenesis in abdominal preadipocytes only; 50 ng/ml BMP2 increased PPARG2 expression (10-fold compared to vehicle, p < 0.001) and TAG accumulation (3-fold compared to vehicle; p < 0.001). BMP2 stimulated SMAD1/5/8 phosphorylation and ID1 expression in abdominal and gluteal preadipocytes but this was blocked by 500 nM K02288, a type 1 BMP receptor inhibitor (p < 0.001). Co-administration of 500 nM K02288 also inhibited the pro-adipogenic effect of 50 ng/ml BMP2 in abdominal cells; >90% inhibition of TAG accumulation (p < 0.001) and ~50% inhibition of PPARG2 expression (p < 0.001). The endogenous iron regulator erythroferrone reduced BMP2-SMAD1/5/8 signalling by ~30% specifically in subcutaneous abdominal preadipocytes (p < 0.01), suggesting it plays a role in restricting the expansion of the body's largest AT depot during energy deficiency. Additionally, a waist-hip ratio-increasing common polymorphism near BMP2 is an eQTL associated with ~15% lower BMP2 expression in abdominal and gluteal AT (p < 0.05) as well as altered adipocyte size in male abdominal AT (p < 0.05).

CONCLUSIONS

These data implicate BMP2-SMAD1/5/8 signalling in depot-specific preadipocyte development and abdominal AT expansion in humans.

Novel genetic loci affecting facial shape variation in humans

The human face represents a combined set of highly heritable phenotypes, but knowledge on its genetic architecture remains limited, despite the relevance for various fields. A series of genome-wide association studies on 78 facial shape phenotypes quantified from 3-dimensional facial images of 10,115 Europeans identified 24 genetic loci reaching study-wide suggestive association (p < 5 × 10-8), among which 17 were previously unreported. A follow-up multi-ethnic study in additional 7917 individuals confirmed 10 loci including six unreported ones (padjusted < 2.1 × 10-3). A global map of derived polygenic face scores assembled facial features in major continental groups consistent with anthropological knowledge. Analyses of epigenomic datasets from cranial neural crest cells revealed abundant cis-regulatory activities at the face-associated genetic loci. Luciferase reporter assays in neural crest progenitor cells highlighted enhancer activities of several face-associated DNA variants. These results substantially advance our understanding of the genetic basis underlying human facial variation and provide candidates for future in-vivo functional studies.

Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers

Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.

Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse

The Jeju horse, indigenous to the Jeju Island in Korea may have originated from Mongolian horses. Adaptations to the local harsh environment have conferred Jeju horse with unique traits such as small-sized body, stocky head, and shorter limbs. These characteristics have not been studied previously at the genomic level. Therefore, we sequenced and compared the genome of 41 horses belonging to 6 breeds. We identified numerous breed-specific non-synonymous SNPs and loss-of-function mutants. Demographic and admixture analyses showed that, though Jeju horse is genetically the closest to the Mongolian breeds, its genetic ancestry is independent of that of the Mongolian breeds. Genome wide selection signature analysis revealed that genes such as LCORL, MSTN, HMGA2, ZFAT, LASP1, PDK4, and ACTN2, were positively selected in the Jeju horse. RNAseq analysis showed that several of these genes were also differentially expressed in Jeju horse compared to Thoroughbred horse. Comparative muscle fiber analysis showed that, the type I muscle fibre content was substantially higher in Jeju horse compared to Thoroughbred horse. Our results provide insights about the selection of complex phenotypic traits in the small-sized Jeju horse and the novel SNPs identified will aid in designing high-density SNP chip for studying other native horse breeds.

Genomic interrogation of familial short stature contributes to the discovery of the pathophysiological mechanisms and pharmaceutical drug repositioning

Background

Genetic factors, dysregulation in the endocrine system, cytokine and paracrine factors are implicated in the pathogenesis of familial short stature (FSS). Nowadays, the treatment choice for FSS is limited, with only recombinant human growth hormone (rhGH) being available.

Methods

Herein, starting from the identification of 122 genetic loci related to FSS, we adopted a genetic-driven drug discovery bioinformatics pipeline based on functional annotation to prioritize crucial biological FSS-related genes. These genes were suggested to be potential targets for therapeutics.

Results

We discovered five druggable subnetworks, which contained seven FSS-related genes and 17 druggable targerts.

Conclusions

This study provides a valuable drug repositioning accompanied by corresponding targetable gene clusters for FSS therapy.

PAPP-A and the IGF system in atherosclerosis: what's up, what's down?

Pregnancy-associated plasma protein-A (PAPP-A) is a metalloproteinase with a well-established role in releasing bioactive insulin-like growth factor-1 (IGF-1) from IGF-binding protein-2, -4, and -5 by proteolytic processing of these. The IGF system has repeatedly been suggested to be involved in the pathology of atherosclerosis, and both PAPP-A and IGF-1 are proposed biomarkers and therapeutic targets for this disease. Several experimental approaches based on atherosclerosis mouse models have been undertaken to obtain causative and mechanistic insight to the role of these molecules in atherogenesis. However, reports seem conflicting. The literature suggests that PAPP-A is detrimental, while IGF-1 is beneficial. This raises important questions that need to be addressed. Here we summarize the various studies and discuss potential underlying explanations for this seemingly inconsistency with the objective of better understanding complexities and limitations when manipulating the IGF system in mouse models of atherosclerosis. A debate clarifying what's up and what's down is highly warranted going forward with the ultimate goal of improving atherosclerosis therapy by targeting the IGF system.

ESR1 polymorphism (rs2234693) influences femoral bone mass in patients with Turner syndrome

Most patients with Turner syndrome (TS) need hormone replacement therapy because of hypergonadotropic hypogonadism; individual outcomes, however, are highly variable. Our objective was to assess the influence of five estrogen receptor 1 gene (ESR1) polymorphisms (rs543650, rs1038304, rs2046210, rs2234693 and rs9340799) on adult height, breast development, uterine volume and bone mineral density (BMD). We studied 91 TS patients from a tertiary hospital using adult estrogen dose. In our group, ESR1 rs2234693 was associated with femoral neck and total hip BMD, and it accounted for around 10% of BMD variability in both sites (P < 0.01). Patients homozygous for C allele in this polymorphism had significantly lower femoral neck BMD (0.699 ± 0.065 g/cm2 vs 0.822 ± 0.113 g/cm2, P = 0.008) and total hip BMD (0.777 ± 0.118 g/cm2 vs 0.903 ± 0.098 g/cm2, P = 0.009) than patients homozygous for T allele. The other four ESR1 polymorphisms were not able to predict any of the above estrogen therapy outcomes in an isolated manner. Patients homozygous for the haplotype GCG formed by polymorphisms rs543650, rs2234693 and rs9340799 had an even more significantly lower femoral neck BMD (0.666 ± 0.049 vs 0.820 ± 0.105 g/cm2, P = 0.0047) and total hip BMD (0.752 ± 0.093 vs 0.908 ± 0.097 g/cm2, P = 0.0029) than patients homozygous for haplotypes with a T allele in rs2234693. In conclusion, homozygosity for C allele in ESR1 rs2234693 and/or for GCG haplotype appears to be associated with lower femoral neck and total hip BMD. We believe that the identification of polymorphisms related to estrogen outcomes may contribute to individualization of treatment in TS.

Sex-dependent and sex-independent regulatory systems of size variation in natural populations

Size of organs/organisms is a polygenic trait. Many of the growth-regulatory genes constitute conserved growth signaling pathways. However, how these multiple genes are orchestrated at the systems level to attain the natural variation in size including sexual size dimorphism is mostly unknown. Here we take a multi-layered systems omics approach to study size variation in the Drosophila wing. We show that expression levels of many critical growth regulators such as Wnt and TGFβ pathway components significantly differ between sexes but not between lines exhibiting size differences within each sex, suggesting a primary role of these regulators in sexual size dimorphism. Only a few growth genes including a receptor of steroid hormone ecdysone exhibit association with between-line size differences. In contrast, we find that between-line size variation is largely regulated by genes with a diverse range of cellular functions, most of which have never been implicated in growth. In addition, we show that expression quantitative trait loci (eQTLs) linked to these novel growth regulators accurately predict population-wide, between-line wing size variation. In summary, our study unveils differential gene regulatory systems that control wing size variation between and within sexes.

Genetic mapping of distal femoral, stifle, and tibial radiographic morphology in dogs with cranial cruciate ligament disease

Cranial cruciate ligament disease (CCLD) is a complex trait. Ten measurements were made on orthogonal distal pelvic limb radiographs of 161 pure and mixed breed dogs with, and 55 without, cranial cruciate partial or complete ligament rupture. Dogs with CCLD had significantly smaller infrapatellar fat pad width, higher average tibial plateau angle, and were heavier than control dogs. The first PC weightings captured the overall size of the dog’s stifle and PC2 weightings reflected an increasing tibial plateau angle coupled with a smaller fat pad width. Of these dogs, 175 were genotyped, and 144,509 polymorphisms were used in a genome-wide association study with both a mixed linear and a multi-locus model. For both models, significant (p_genome <3.46×10⁻⁷ for the mixed and< 6.9x10^-8 for the multilocus model) associations were found for PC1, tibial diaphyseal length and width, fat pad base length, and femoral and tibial condyle width at LCORL, a known body size-regulating locus. Other body size loci with significant associations were growth hormone 1 (GH1), which was associated with the length of the fat pad base and the width of the tibial diaphysis, and a region on CFAX near IRS4 and ACSL4 in the multilocus model. The tibial plateau angle was associated significantly with a locus on CFA10 in the linear mixed model with nearest candidate genes BET1 and MYH9 and on CFA08 near candidate genes WDHD1 and GCH1. MYH9 has a major role in osteoclastogenesis. Our study indicated that tibial plateau slope is associated with CCLD and a compressed infrapatellar fat pad, a surrogate for stifle osteoarthritis. Because of the association between tibial plateau slope and CCLD, and pending independent validation, these candidate genes for tibial plateau slope may be tested in breeds susceptible to CCLD before they develop disease or are bred.

Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits

Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect size genes could cumulatively play a substantial role in pathway function. Here, we determine the number, strength, and identity of all non-essential test genes that affect two quantitative galactose-responsive traits in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect size alleles are capable of contributing more to trait variation than alleles in a canonical, large effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.

Could consanguineous marriage provide a cultural alleviation for the obstetric dilemma?

In placental mammals, a poor fit between the physical dimensions of the fetus and maternal pelvis increases the likelihood of obstructed labour. This problem is especially relevant to humans, as our species demonstrates both unique adaptations in pelvic shape and structure associated with bipedalism, and fetal encephalization. Natural selection is expected to have favoured adaptations that reduce the chances of such mismatch within individual mother-offspring dyads. Here, I hypothesise that the cultural practice of consanguineous marriage may have been favoured, on account of increasing the genetic similarity between mothers and offspring and hence the correlation between maternal and fetal physical dimensions. These benefits could be amplified if consanguineous marriage was accompanied by assortative mating for height. An additional benefit of consanguineous marriage for childbirth is the slight reduction in birth size of such offspring compared to non-consanguineous unions. Although the offspring of consanguineous unions have elevated risks of morbidity and mortality, these risks are moderate and the practice could still have been favoured by selection if the reduction in maternal mortality was greater than the increased mortality among individual offspring. This hypothesis could be tested directly by investigating whether rates of obstructed labour are lower in individuals and populations practising consanguineous marriage. At a broader level, phylogenetic analysis could be conducted to test whether consanguineous marriage appears to have originated in the areas where intensive agriculture was first practiced, as adult height typically fell in such populations, potentially exacerbating the risk of obstructed labour.

Bayesian multivariate reanalysis of large genetic studies identifies many new associations

Genome-wide association studies (GWAS) have now been conducted for hundreds of phenotypes of relevance to human health. Many such GWAS involve multiple closely-related phenotypes collected on the same samples. However, the vast majority of these GWAS have been analyzed using simple univariate analyses, which consider one phenotype at a time. This is despite the fact that, at least in simulation experiments, multivariate analyses have been shown to be more powerful at detecting associations. Here, we conduct multivariate association analyses on 13 different publicly-available GWAS datasets that involve multiple closely-related phenotypes. These data include large studies of anthropometric traits (GIANT), plasma lipid traits (GlobalLipids), and red blood cell traits (HaemgenRBC). Our analyses identify many new associations (433 in total across the 13 studies), many of which replicate when follow-up samples are available. Overall, our results demonstrate that multivariate analyses can help make more effective use of data from both existing and future GWAS.

Genome-wide association studies (GWAS) have become a common and powerful tool for identifying significant correlations between markers of genetic variation and physical traits of interest. Often these studies are conducted by comparing genetic variation against single traits one at a time (‘univariate’); however, it has previously been shown that it is possible to increase your power to detect significant associations by comparing genetic variation against multiple traits simultaneously (‘multivariate’). Despite this apparent increase in power though, researchers still rarely conduct multivariate GWAS, even when studies have multiple traits readily available. Here, we reanalyze 13 previously published GWAS using a multivariate method and find >400 additional associations. Our method makes use of univariate GWAS summary statistics and is available as a software package, thus making it accessible to other researchers interested in conducting the same analyses. We also show, using studies that have multiple releases, that our new associations have high rates of replication. Overall, we argue multivariate approaches in GWAS should no longer be overlooked and how, often, there is low-hanging fruit in the form of new associations by running these methods on data already collected.

Genetic contributions to variation in human stature in prehistoric Europe

Measurements of prehistoric human skeletal remains provide a record of changes in height and other anthropometric traits over time. Often, these changes are interpreted in terms of plastic developmental response to shifts in diet, climate, or other environmental factors. These changes can also be genetic in origin, but, until recently, it has been impossible to separate the effects of genetics and environment. Here, we use ancient DNA to directly estimate genetic changes in phenotypes and to identify changes driven not by genetics, but by environment. We show that changes over the past 35,000 y are largely predicted by genetics but also identify specific shifts that are more likely to be environmentally driven.

The relative contributions of genetics and environment to temporal and geographic variation in human height remain largely unknown. Ancient DNA has identified changes in genetic ancestry over time, but it is not clear whether those changes in ancestry are associated with changes in height. Here, we directly test whether changes over the past 38,000 y in European height predicted using DNA from 1,071 ancient individuals are consistent with changes observed in 1,159 skeletal remains from comparable populations. We show that the observed decrease in height between the Early Upper Paleolithic and the Mesolithic is qualitatively predicted by genetics. Similarly, both skeletal and genetic height remained constant between the Mesolithic and Neolithic and increased between the Neolithic and Bronze Age. Sitting height changes much less than standing height—consistent with genetic predictions—although genetics predicts a small post-Neolithic increase that is not observed in skeletal remains. Geographic variation in stature is also qualitatively consistent with genetic predictions, particularly with respect to latitude. Finally, we hypothesize that an observed decrease in genetic heel bone mineral density in the Neolithic reflects adaptation to the decreased mobility indicated by decreased femoral bending strength. This study provides a model for interpreting phenotypic changes predicted from ancient DNA and demonstrates how they can be combined with phenotypic measurements to understand the relative contribution of genetic and developmentally plastic responses to environmental change.

A flexible and parallelizable approach to genome-wide polygenic risk scores

The heritability of most complex traits is driven by variants throughout the genome. Consequently, polygenic risk scores, which combine information on multiple variants genome-wide, have demonstrated improved accuracy in genetic risk prediction. We present a new two-step approach to constructing genome-wide polygenic risk scores from meta-GWAS summary statistics. Local linkage disequilibrium (LD) is adjusted for in Step 1, followed by, uniquely, long-range LD in Step 2. Our algorithm is highly parallelizable since block-wise analyses in Step 1 can be distributed across a high-performance computing cluster, and flexible, since sparsity and heritability are estimated within each block. Inference is obtained through a formal Bayesian variable selection framework, meaning final risk predictions are averaged over competing models. We compared our method to two alternative approaches: LDPred and lassosum using all seven traits in the Welcome Trust Case Control Consortium as well as meta-GWAS summaries for type 1 diabetes (T1D), coronary artery disease, and schizophrenia. Performance was generally similar across methods, although our framework provided more accurate predictions for T1D, for which there are multiple heterogeneous signals in regions of both short- and long-range LD. With sufficient compute resources, our method also allows the fastest runtimes.

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.

Methylation of the C19MC microRNA locus in the placenta: association with maternal and chilhood body size

OBJECTIVES

To study DNA methylation at the C19MC locus in the placenta and its association with (1) parental body size, (2) transmission of haplotypes for the C19MC rs55765443 SNP, and (3) offspring's body size and/or body composition at birth and in childhood.

SUBJECTS AND METHODS

Seventy-two pregnant women-infant pairs and 63 fathers were included in the study. Weight and height of mothers, fathers and newborns were registered during pregnancy or at birth (n = 72). Placental DNA methylation at the C19MC imprinting control region (ICR) was quantified by bisulfite pyrosequencing. Genotyping of the SNP was performed using restriction fragment length polymorphisms. The children's body size and composition were reassessed at age 6 years (n = 32).

RESULTS

Lower levels of placental C19MC methylation were associated with increased body size of mother, specifically with higher pregestational and predelivery weights and height of the mother (β from -0.294 to -0.371; R² from 0.04 to 0.10 and all p < 0.019), and with higher weight, height, waist and hip circumferences, and fat mass of the child (β from -0.428 to -0.552; R² from 0.33 to 0.56 and all p < 0.009). Parental transmission of the SNP did not correlate with an altered placental methylation status at the C19MC ICR.

CONCLUSIONS

Increased maternal size is associated with reduced placental C19MC methylation, which, in turn, relate to larger body size of the child.

Summary statistic analyses can mistake confounding bias for heritability

Linkage disequilibrium SCore regression (LDSC) has become a popular approach to estimate confounding bias, heritability, and genetic correlation using only genome-wide association study (GWAS) test statistics. SumHer is a newly introduced alternative with similar aims. We show using theory and simulations that both approaches fail to adequately account for confounding bias, even when the assumed heritability model is correct. Consequently, these methods may estimate heritability poorly if there was an inadequate adjustment for confounding in the original GWAS analysis. We also show that the choice of a summary statistic for use in LDSC or SumHer can have a large impact on resulting inferences. Further, covariate adjustments in the original GWAS can alter the target of heritability estimation, which can be problematic for test statistics from a meta-analysis of GWAS with different covariate adjustments.

Reaffirmation of known major genes and the identification of novel candidate genes associated with carcass-related metrics based on whole genome sequence within a large multi-breed cattle population

Background

The high narrow sense heritability of carcass traits suggests that the underlying additive genetic potential of an individual should be strongly correlated with both animal carcass quality and quantity, and therefore, by extension, carcass value. Therefore, the objective of the present study was to detect genomic regions associated with three carcass traits, namely carcass weight, conformation and fat cover, using imputed whole genome sequence in 28,470 dairy and beef sires from six breeds with a total of 2,199,926 phenotyped progeny.

Results

Major genes previously associated with carcass performance were identified, as well as several putative novel candidate genes that likely operate both within and across breeds. The role of MSTN in carcass performance was re-affirmed with the segregating Q204X mutation explaining 1.21, 1.11 and 5.95% of the genetic variance in carcass weight, fat and conformation, respectively in the Charolais population. In addition, a genomic region on BTA6 encompassing the NCAPG/LCORL locus, which is a known candidate locus associated with body size, was associated with carcass weight in Angus, Charolais and Limousin. Novel candidate genes identified included ZFAT in Angus, and SLC40A1 and the olfactory gene cluster on BTA15 in Charolais. Although the majority of associations were breed specific, associations that operated across breeds included SORCS1 on BTA26, MCTP2 on BTA21 and ARL15 on BTA20; these are of particular interest due to their potential informativeness in across-breed genomic evaluations. Genomic regions affecting all three carcass traits were identified in each of the breeds, although these were mainly concentrated on BTA2 and BTA6, surrounding MSTN and NCAPG/LCORL, respectively. This suggests that although major genes may be associated with all three carcass traits, the majority of genes containing significant variants (unadjusted p-value < 10^− 4) may be trait specific associations of small effect.

Conclusions

Although plausible novel candidate genes were identified, the proportion of variance explained by these candidates was minimal thus reaffirming that while carcass performance may be affected by major genes in the form of MSTN and NCAPG/LCORL, the majority of variance is attributed to the additive (and possibly multiplicative) effect of many polymorphisms of small effect.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6071-9) contains supplementary material, which is available to authorized users.

Imputation of canine genotype array data using 365 whole-genome sequences improves power of genome-wide association studies

Genomic resources for the domestic dog have improved with the widespread adoption of a 173k SNP array platform and updated reference genome. SNP arrays of this density are sufficient for detecting genetic associations within breeds but are underpowered for finding associations across multiple breeds or in mixed-breed dogs, where linkage disequilibrium rapidly decays between markers, even though such studies would hold particular promise for mapping complex diseases and traits. Here we introduce an imputation reference panel, consisting of 365 diverse, whole-genome sequenced dogs and wolves, which increases the number of markers that can be queried in genome-wide association studies approximately 130-fold. Using previously genotyped dogs, we show the utility of this reference panel in identifying potentially novel associations, including a locus on CFA20 significantly associated with cranial cruciate ligament disease, and fine-mapping for canine body size and blood phenotypes, even when causal loci are not in strong linkage disequilibrium with any single array marker. This reference panel resource will improve future genome-wide association studies for canine complex diseases and other phenotypes.

Complex traits are controlled by more than one gene and as such are difficult to map. For complex trait mapping in the domestic dog, researchers use the current array of 173,000 variants, with only minimal success. Here, we use a method called imputation to increase the number of variants–from 173,000 to 24 million–that can be queried in canine association studies. We use sequence data from the whole genomes of 365 dogs and wolves to accurately predict variants, in a separate cohort of dogs, that are not present on the array. Using dog body size, blood phenotypes, and a common orthopedic disease that involves rupture of the cranial cruciate ligament, we show that the increase in variants results in an increase in mapping power, through the identification of new associations and the narrowing of regions of interest. This imputation panel is particularly important because of its usefulness in improving complex trait mapping in the dog, which has significant implications for discovery of variants in humans with similar diseases.

A Novel 13 bp Deletion within the NR6A1 Gene Is Significantly Associated with Growth Traits in Donkeys

Simple Summary

The detection of genes potentially associated with economic traits and identification of effective variants can provide a basis for molecular marker-assisted selection of livestock. NR6A1 is a member of the nuclear receptor family and is an important candidate gene related to body size traits. Previous studies showed that NR6A1 gene was associated with body size traits in pigs and other livestock, however, it has not yet been observed in donkeys. In the current study, a 13 bp deletion in NR6A1 gene was firstly identified in donkeys. Analysis showed that this deletion had significant associations with body size traits.

Abstract

Nuclear receptor subfamily 6, group A, member 1 (NR6A1), as an important member of the nuclear receptor family, plays an important role in regulating growth, metabolism, and differentiation of embryonic stem cells. For this reason, the NR6A1 gene is considered to be a promising candidate for economic traits and was found to be associated with body size traits in many livestock. However, no studies have been conducted on NR6A1 in donkeys so far. Thus, in this research, we focused on donkeys and identified a 13 bp deletion in intron-1 of the NR6A1 gene among 408 individuals from Guanzhong and Dezhou donkeys using polyacrylamide gel electrophoresis. Three genotypes were identified, namely II, ID, and DD. The association analysis indicated that the body lengths and body heights5f genotype II individuals were significantly different to those of genotype ID in Dezhou donkeys. Conclusively, the 13 bp deletion was associated with growth traits in both Guanzhong donkeys and Dezhou donkeys, indicating that the NR6A1 gene could be a possible candidate gene in marker-assisted selection for donkey breeding programs.

A general statistic to test an optimally weighted combination of common and/or rare variants

Both genome-wide association study and next-generation sequencing data analyses are widely employed to identify disease susceptible common and/or rare genetic variants. Rare variants generally have large effects though they are hard to detect due to their low frequencies. Currently, many existing statistical methods for rare variants association studies employ a weighted combination scheme, which usually puts subjective weights or suboptimal weights based on some adhoc assumptions (e.g., ignoring dependence between rare variants). In this study, we analytically derived optimal weights for both common and rare variants and proposed a general and novel approach to test association between an optimally weighted combination of variants (G-TOW) in a gene or pathway for a continuous or dichotomous trait while easily adjusting for covariates. Results of the simulation studies show that G-TOW has properly controlled type I error rates and it is the most powerful test among the methods we compared when testing effects of either both rare and common variants or rare variants only. We also illustrate the effectiveness of G-TOW using the Genetic Analysis Workshop 17 (GAW17) data. Additionally, we applied G-TOW and other competitive methods to test disease-associated genes in real data of schizophrenia. The G-TOW has successfully verified genes FYN and VPS39 which are associated with schizophrenia reported in existing publications. Both of these genes are missed by the weighted sum statistic and the sequence kernel association test. Simulation study and real data analysis indicate that G-TOW is a powerful test.

Healthy diet is associated with gene expression in blood: the Framingham Heart Study

BACKGROUND

Genes in metabolic and nutrient signaling pathways play important roles in lifespan in model organisms and human longevity.

OBJECTIVE

The aim of this study was to examine the relation of a quantitative measure of healthy diet to gene expression in a community-based cohort.

METHODS

We used the 2015 Dietary Guidelines for Americans Adherence Index (DGAI) score to quantify key dietary recommendations of an overall healthy diet. Our current analyses included 2220 Offspring participants (mean age 66 ± 9 y, 55.4% women) and 2941 Third-Generation participants (mean age 46 ± 9 y, 54.5% women) from the Framingham Heart Study. Gene expression was profiled in blood through the use of the Affymetrix Human Exon 1.0 ST Array. We conducted a transcriptome-wide association study of DGAI adjusting for age, sex, smoking, cell counts, and technical covariates. We also constructed a combined gene score from genes significantly associated with DGAI.

RESULTS

The DGAI was significantly associated with the expression of 19 genes (false discovery rate <0.05). The most significant gene, ARRDC3, is a member of the arrestin family of proteins, and evidence in animal models and human data suggests that this gene is a regulator of obesity and energy expenditure. The DGAI gene score was associated with body mass index (P = 1.4 × 10-50), fasting glucose concentration (P = 2.5 × 10-11), type 2 diabetes (P = 1.1 × 10-5), and metabolic syndrome (P = 1.8 × 10-32).

CONCLUSIONS

Healthier diet was associated with genes involved in metabolic function. Further work is needed to replicate our findings and investigate the relation of a healthy diet to altered gene regulation.

A unifying framework for joint trait analysis under a non-infinitesimal model

Motivation

A large proportion of risk regions identified by genome-wide association studies (GWAS) are shared across multiple diseases and traits. Understanding whether this clustering is due to sharing of causal variants or chance colocalization can provide insights into shared etiology of complex traits and diseases.

Results

In this work, we propose a flexible, unifying framework to quantify the overlap between a pair of traits called UNITY (Unifying Non-Infinitesimal Trait analYsis). We formulate a Bayesian generative model that relates the overlap between pairs of traits to GWAS summary statistic data under a non-infinitesimal genetic architecture underlying each trait. We propose a Metropolis-Hastings sampler to compute the posterior density of the genetic overlap parameters in this model. We validate our method through comprehensive simulations and analyze summary statistics from height and body mass index GWAS to show that it produces estimates consistent with the known genetic makeup of both traits.

Availability and implementation

The UNITY software is made freely available to the research community at: https://github.com/bogdanlab/UNITY.

Supplementary information

Supplementary data are available at Bioinformatics online.