Backgroud

The role of cyclooxygenase-2 (COX-2) single nucleotide polymorphisms has mostly been studied in relation to advanced atherosclerosis, but little is known how they contribute to preclinical disease. In the present study we analyzed whether COX-2 gene variants associate independently with the early subclinical markers of atherosclerosis, carotid intima-media thickness and carotid artery distensibility in a population of young healthy Caucasian adults.

Methods

SNPs for association analysis were collected from the COX-2 gene and 5 kb up- and downstream of it. There were 19 SNPs available for analysis, four genotyped and fifteen imputed. Genotype data was available for 2442 individuals participating in the Cardiovascular Risk in Young Finns Study. Genotype imputation was performed using MACH 1.0 and HapMap II CEU (release 22) samples as reference. Association analysis was performed using linear regression with an additive model. PLINK was used for true genotyped SNPs and ProbABEL for imputed genotype dosages. False discovery rate was used to take into account multiple testing bias.

Results

Two of the COX-2 variants (rs689470, rs689462) associated with distensibility (p = 0.005) under the linear regression additive model. After adjustment with gender, age, body mass index and smoking status, association between these SNPs and distensibility remained significant (p = 0.031). Subjects carrying the minor alleles had higher value of carotid artery distensibility compared to the major allele homozygotes. However, after correcting p-values for multiple testing bias using false discovery rate, association was lost. Another COX-2 variant rs4648261 associated with mean carotid intima-media thickness (p = 0.046) and maximal carotid intima-media thickness (p = 0.048) in the linear regression model. Subjects carrying the minor allele of rs4648261 had lower values of mean and maximal carotid intima-media thickness compared to subjects homozygote for major allele. After adjustments the associations were lost with both mean and maximal carotid intima-media thickness. Thus, no statistically significant associations of the studied COX-2 variants with carotid artery distensibility or carotid intima-media thickness were found.

Conclusions

Our results suggest that in a Finnish population, there are no significant associations between COX-2 variants and early atherosclerotic changes in young adulthood.

Most previous genetic epidemiology studies within the field of osteoporosis have focused on the genetics of the complex trait areal bone mineral density (aBMD), not being able to differentiate genetic determinants of cortical volumetric BMD (vBMD), trabecular vBMD, and bone microstructural traits. The objective of this study was to separately identify genetic determinants of these bone traits as analysed by peripheral quantitative computed tomography (pQCT). Separate GWA meta-analyses for cortical and trabecular vBMDs were performed. The cortical vBMD GWA meta-analysis (n = 5,878) followed by replication (n = 1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, p = 3.6×10−14; LOC285735, rs271170, p = 2.7×10−12; OPG, rs7839059, p = 1.2×10−10; and ESR1/C6orf97, rs6909279, p = 1.1×10−9). The trabecular vBMD GWA meta-analysis (n = 2,500) followed by replication (n = 1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, p = 1.9×10−9). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (n = 729). rs1021188 was significantly associated with cortical porosity while rs9287237 was significantly associated with trabecular bone fraction. The genetic variant in the FMN2/GREM2 locus was associated with fracture risk in the MrOS Sweden cohort (HR per extra T allele 0.75, 95% confidence interval 0.60–0.93) and GREM2 expression in human osteoblasts. In conclusion, five genetic loci associated with trabecular or cortical vBMD were identified. Two of these (FMN2/GREM2 and LOC285735) are novel bone-related loci, while the other three have previously been reported to be associated with aBMD. The genetic variants associated with cortical and trabecular bone parameters differed, underscoring the complexity of the genetics of bone parameters. We propose that a genetic variant in the RANKL locus influences cortical vBMD, at least partly, via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences GREM2 expression in osteoblasts and thereby trabecular number and thickness as well as fracture risk.

Author Summary

Osteoporosis is a common highly heritable skeletal disease characterized by reduced bone mineral density (BMD) and deteriorated bone microstructure, resulting in an increased risk of fracture. Most previous genetic epidemiology studies have focused on the genetics of the complex trait BMD, not being able to separate genetic determinants of the trabecular and cortical bone compartments and bone microstructure. The trabecular and cortical BMDs can be analysed separately by computed tomography. Therefore, we performed separate genome-wide association studies for trabecular and cortical BMDs, demonstrating that the genetic determinants of cortical and trabecular BMDs differ. Genetic variants in the RANKL, LOC285735, OPG, and ESR1 loci were associated with cortical BMD, while a genetic variant in the FMN2/GREM2 locus was associated with trabecular BMD. Two of these are novel bone-related loci. Follow-up analyses of bone microstructure demonstrated that a genetic variant in the RANKL locus is associated with cortical porosity and that the FMN2/GREM2 locus is associated with trabecular number and thickness. We propose that a genetic variant in the RANKL locus influences cortical BMD via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences trabecular BMD and fracture risk via effects on both trabecular number and thickness.

Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.

Author Summary

In this study, we aim to identify novel genetic variants for metabolism, characterize their effects on nearby genes, and show that the nearby genes are associated with metabolism and atherosclerosis. To discover new genetic variants, we use an alternative approach to traditional genome-wide association studies: we leverage the information in phenotype covariance to increase our statistical power. We identify variants at seven novel loci and then show that our top signals drive expression of nearby genes AQP9 and SERPINA1 in multiple tissues. We demonstrate that AQP9 and SERPINA1 gene expression, in turn, is associated with metabolite levels. Finally, we show that the genes are associated with atherosclerosis using mouse atherosclerotic lesion size (AQP9) as well as tissue from healthy human arteries and atherosclerotic plaques (AQP9 and SERPINA1). This study illustrates that multivariate analysis of correlated metabolites can boost power for gene discovery substantially. Further functional work will need to be performed to elucidate the biological role of SERPINA1 and AQP9 in atherosclerosis.

Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.

Author Summary

Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Author Summary

Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting the sex steroid hormones, testosterone and estradiol, in the circulatory system. SHBG regulates their bioavailability and therefore their effects in the body. SHBG has been linked to chronic diseases including type 2 diabetes and to hormone-sensitive cancers such as breast and prostate cancer. SHBG concentrations are approximately 50% heritable in family studies, suggesting SHBG concentrations are under significant genetic control; yet, little is known about the specific genes that influence SHBG. We conducted a large study of the association of SHBG concentrations with markers in the human genome in ∼22,000 white men and women to determine which loci influence SHBG concentrations. Genes near the identified genomic markers in addition to the SHBG protein coding gene included PRMT6, GCKR, ZBTB10, JMJD1C, SLCO1B1, NR2F2, ZNF652, TDGF3, LHCGR, BAIAP2L1, and UGT2B15. These genes represent a wide range of biologic pathways that may relate to SHBG function and sex steroid hormone biology, including liver function, lipid metabolism, carbohydrate metabolism and type 2 diabetes, and the development and progression of sex steroid hormone-responsive cancers.

We aimed to identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) by performing two separate genome-wide association study (GWAS) meta-analyses for CBT in 3 cohorts comprising 5,878 European subjects and for BMD in 5 cohorts comprising 5,672 individuals. We then assessed selected single-nucleotide polymorphisms (SNPs) for osteoporotic fracture in 2,023 cases and 3,740 controls. Association with CBT and forearm BMD was tested for ∼2.5 million SNPs in each cohort separately, and results were meta-analyzed using fixed effect meta-analysis. We identified a missense SNP (Thr>Ile; rs2707466) located in the WNT16 gene (7q31), associated with CBT (effect size of −0.11 standard deviations [SD] per C allele, P = 6.2×10−9). This SNP, as well as another nonsynonymous SNP rs2908004 (Gly>Arg), also had genome-wide significant association with forearm BMD (−0.14 SD per C allele, P = 2.3×10−12, and −0.16 SD per G allele, P = 1.2×10−15, respectively). Four genome-wide significant SNPs arising from BMD meta-analysis were tested for association with forearm fracture. SNP rs7776725 in FAM3C, a gene adjacent to WNT16, was associated with a genome-wide significant increased risk of forearm fracture (OR = 1.33, P = 7.3×10−9), with genome-wide suggestive signals from the two missense variants in WNT16 (rs2908004: OR = 1.22, P = 4.9×10−6 and rs2707466: OR = 1.22, P = 7.2×10−6). We next generated a homozygous mouse with targeted disruption of Wnt16. Female Wnt16−/− mice had 27% (P<0.001) thinner cortical bones at the femur midshaft, and bone strength measures were reduced between 43%–61% (6.5×10−13

Author Summary

Bone traits are highly dependent on genetic factors. To date, numerous genetic loci for bone mineral density (BMD) and only one locus for osteoporotic fracture have been previously identified to be genome-wide significant. Cortical bone has been reported to be an important determinant of bone strength; so far, no genome-wide association studies (GWAS) have been performed for cortical bone thickness (CBT) of the tibial and radial diaphysis or BMD at forearm, a skeletal site rich in cortical bone. Therefore, we performed two separated meta-analyses of GWAS for cortical thickness of the tibia in 3 independent cohorts of 5,878 men and women, and for forearm BMD in 5 cohorts of 5,672 individuals. We identified the 7q31 locus, which contains WNT16, to be associated with CBT and BMD. Four SNPs from this locus were then tested in 2,023 osteoporotic fracture cases and 3,740 controls. One of these SNPs was genome-wide significant, and two were genome-wide suggestive, for forearm fracture. Generating a mouse with targeted disruption of Wnt16, we also demonstrated that mice lacking this protein had substantially thinner bone cortices and reduced bone strength than their wild-type littermates. These findings highlight WNT16 as a clinically relevant member of the Wnt signaling pathway and increase our understanding of the etiology of osteoporosis-related phenotypes and fracture.