Functional Genomics Complements Quantitative Genetics in Identifying Disease-Gene Associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype

A circadian-regulated gene, Nocturnin, promotes adipogenesis by stimulating PPAR- nuclear translocation

Nocturnin (NOC) is a circadian-regulated protein related to the yeast family of transcription factors involved in the cellular response to nutrient status. In mammals, NOC functions as a deadenylase but lacks a transcriptional activation domain. It is highly expressed in bone-marrow stromal cells (BMSCs), hepatocytes, and adipocytes. In BMSCs exposed to the PPAR-γ (peroxisome proliferator-activated receptor-γ) agonist rosiglitazone, Noc expression was enhanced 30-fold. Previously, we reported that Noc−/− mice had low body temperature, were protected from diet-induced obesity, and most importantly exhibited absence of Pparg circadian rhythmicity on a high-fat diet. Consistent with its role in influencing BMSCs allocation, Noc−/− mice have reduced bone marrow adiposity and high bone mass. In that same vein, NOC overexpression enhances adipogenesis in 3T3-L1 cells but negatively regulates osteogenesis in MC3T3-E1 cells. NOC and a mutated form, which lacks deadenylase activity, bind to PPAR-γ and markedly enhance PPAR-γ transcriptional activity. Both WT and mutant NOC facilitate nuclear translocation of PPAR-γ. Importantly, NOC-mediated nuclear translocation of PPAR-γ is blocked by a short peptide fragment of NOC that inhibits its physical interaction with PPAR-γ. The inhibitory effect of this NOC-peptide was partially reversed by rosiglitazone, suggesting that effect of NOC on PPAR-γ nuclear translocation may be independent of ligand-mediated PPAR-γ activation. In sum, Noc plays a unique role in the regulation of mesenchymal stem-cell lineage allocation by modulating PPAR-γ activity through nuclear translocation. These data illustrate a unique mechanism whereby a nutrient-responsive gene influences BMSCs differentiation, adipogenesis, and ultimately body composition

Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study.

OBJECTIVES: To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk. DESIGN: Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach. SETTING: 25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data. PARTICIPANTS: A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor. RESULTS: Of 15 fracture associated loci identified, all were also associated with bone mineral density and mapped to genes clustering in pathways known to be critical to bone biology (eg, SOST, WNT16, and ESR1) or novel pathways (FAM210A, GRB10, and ETS2). Mendelian randomisation analyses showed a clear effect of bone mineral density on fracture risk. One standard deviation decrease in genetically determined bone mineral density of the femoral neck was associated with a 55% increase in fracture risk (odds ratio 1.55 (95% confidence interval 1.48 to 1.63; P=1.5×10-68). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture. CONCLUSIONS: This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk

A Polymorphism in a Gene Encoding Perilipin 4 Is Associated with Height but not with Bone Measures in Individuals from the Framingham Osteoporosis Study

There is increasing interest in identifying new pathways and candidate genes that confer susceptibility to osteoporosis. There is evidence that adipogenesis and osteogenesis may be related, including a common bone marrow progenitor cell for both adipocytes and osteoblasts. Perilipin 1 (PLIN1) and Perilipin 4 (PLIN4) are members of the PATS family of genes and are involved in lipolysis of intracellular lipid deposits. A previous study reported gender-specific associations between one polymorphism of PLIN1 and bone mineral density (BMD) in a Japanese population. We hypothesized that polymorphisms in PLIN1 and PLIN4 would be associated with bone measures in adult Caucasian participants of the Framingham Osteoporosis Study (FOS). We genotyped 1,206 male and 1,445 female participants of the FOS for four single-nucleotide polymorphism (SNPs) in PLIN1 and seven SNPs in PLIN4 and tested for associations with measures of BMD, bone ultrasound, hip geometry, and height. We found several gender-specific significant associations with the measured traits. The association of PLIN4 SNP rs8887, G>A with height in females trended toward significance after simulation testing (adjusted P = 0.07) and remained significant after simulation testing in the combined-sex model (adjusted P = 0.033). In a large study sample of men and women, we found a significant association between one SNP in PLIN4 and height but not with bone traits, suggesting that PATS family genes are not important in the regulation of bone. Identification of genes that influence human height may lead to a better understanding of the processes involved in growth and development

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% for TBLH-BMD, and 39% for TB-LM, with a shared genetic component of 43%. We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: _WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5_. Variants in the _TOM1L2/SREBF1_ locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that _SREBF1_ is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women.

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p = 4 × 10-17), arthritis (GDF5 p = 4 × 10-13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing

Phenotypic Dissection of Bone Mineral Density Reveals Skeletal Site Specificity and Facilitates the Identification of Novel Loci in the Genetic Regulation of Bone Mass Attainment

Heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To quantify the degree to which common genetic variants tag and environmental factors influence BMD, at different sites, we estimated the genetic (rg) and residual (re) correlations between BMD measured at the upper limbs (UL-BMD), lower limbs (LL-BMD) and skull (SK-BMD), using total-body DXA scans of ~4,890 participants recruited by the Avon Longitudinal Study of Parents and their Children (ALSPAC). Point estimates of rg indicated that appendicular sites have a greater proportion of shared genetic architecture (LL-/UL-BMD rg = 0.78) between them, than with the skull (UL-/SK-BMD rg = 0.58 and LL-/SK-BMD rg = 0.43). Likewise, the residual correlation between BMD at appendicular sites (re = 0.55) was higher than the residual correlation between SK-BMD and BMD at appendicular sites (re = 0.20-0.24). To explore the basis fo

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% for TBLH-BMD, and 39% for TB-LM, with a shared genetic component of 43%. We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: _WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5_. Variants in the _TOM1L2/SREBF1_ locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that _SREBF1_ is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass

Bone mineral density loci specific to the skull portray potential pleiotropic effects on craniosynostosis

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of key genes in bone biology, particularly to intramembranous ossification, not captured at other skeletal sites. We perform a genome-wide association meta-analysis (n ~ 43,800) of SK-BMD, identifying 59 loci, collectively explaining 12.5% of the trait variance. Association signals cluster within gene-sets involved in skeletal development and osteoporosis. Among the four novel loci (ZIC1, PRKAR1A, AZIN1/ATP6V1C1, GLRX3), there are factors implicated in intramembranous ossification and as we show, inherent to craniosynostosis processes. Functional follow-up in zebrafish confirms the importance of ZIC1 on cranial suture patterning. Likewise, we observe abnormal cranial bone initiation that culminates in ectopic sutures and reduced BMD in mosaic atp6v1c1 knockouts. Mosaic prkar1a knockouts present asymmetric bone growth and, conversely, elevated BMD. In light of this evidence linking SK-BMD loci to craniofacial abnormalities, our study provides new insight into the pathophysiology, diagnosis and treatment of skeletal diseases. Prevention, Population and Disease management (PrePoD)Public Health and primary car