Joel Eriksson

A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation

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, pu200a=u200a1.8×10−106), PRMT6 (rs17496332, 1p13.3, pu200a=u200a1.4×10−11), GCKR (rs780093, 2p23.3, pu200a=u200a2.2×10−16), ZBTB10 (rs440837, 8q21.13, pu200a=u200a3.4×10−09), JMJD1C (rs7910927, 10q21.3, pu200a=u200a6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, pu200a=u200a1.9×10−08), NR2F2 (rs8023580, 15q26.2, pu200a=u200a8.3×10−12), ZNF652 (rs2411984, 17q21.32, pu200a=u200a3.5×10−14), TDGF3 (rs1573036, Xq22.3, pu200a=u200a4.1×10−14), LHCGR (rs10454142, 2p16.3, pu200a=u200a1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, pu200a=u200a2.7×10−08), and UGT2B15 (rs293428, 4q13.2, pu200a=u200a5.5×10−06). 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 pu200a=u200a2.5×10−08, women pu200a=u200a0.66, heterogeneity pu200a=u200a0.003). 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.

WNT16 influences bone mineral density, cortical bone thickness, bone strength, and osteoporotic fracture risk.

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, Pu200a=u200a6.2×10−9). 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, Pu200a=u200a2.3×10−12, and −0.16 SD per G allele, Pu200a=u200a1.2×10−15, 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 (ORu200a=u200a1.33, Pu200a=u200a7.3×10−9), with genome-wide suggestive signals from the two missense variants in WNT16 (rs2908004: ORu200a=u200a1.22, Pu200a=u200a4.9×10−6 and rs2707466: ORu200a=u200a1.22, Pu200a=u200a7.2×10−6). 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<P<5.9×10−4) at both femur and tibia, compared with their wild-type littermates. Natural variation in humans and targeted disruption in mice demonstrate that WNT16 is an important determinant of CBT, BMD, bone strength, and risk of fracture.

Genetic Determinants of Serum Testosterone Concentrations in Men

Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterones high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (nu200a=u200a871) and two de novo replication cohorts (nu200a=u200a4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as <300 ng/dl. Two single-nucleotide polymorphisms at the sex hormone-binding globulin (SHBG) locus (17p13-p12) were identified as independently associated with serum testosterone concentration (rs12150660, pu200a=u200a1.2×10−41 and rs6258, pu200a=u200a2.3×10−22). Subjects with ≥3 risk alleles of these variants had 6.5-fold higher risk of having low serum testosterone than subjects with no risk allele. The rs5934505 polymorphism near FAM9B on the X chromosome was also associated with testosterone concentrations (pu200a=u200a5.6×10−16). The rs6258 polymorphism in exon 4 of SHBG affected SHBGs affinity for binding testosterone and the measured free testosterone fraction (p<0.01). Genetic variants in the SHBG locus and on the X chromosome are associated with a substantial variation in testosterone concentrations and increased risk of low testosterone. rs6258 is the first reported SHBG polymorphism, which affects testosterone binding to SHBG and the free testosterone fraction and could therefore influence the calculation of free testosterone using law-of-mass-action equation.

Meta-analysis of genome-wide scans for total body BMD in children and adults reveals allelic heterogeneity and age-specific effects at the WNT16 locus

To identify genetic loci influencing bone accrual, we performed a genome-wide association scan for total-body bone mineral density (TB-BMD) variation in 2,660 children of different ethnicities. We discovered variants in 7q31.31 associated with BMD measurements, with the lowest Pu200a=u200a4.1×10−11 observed for rs917727 with minor allele frequency of 0.37. We sought replication for all SNPs located ±500 kb from rs917727 in 11,052 additional individuals from five independent studies including children and adults, together with de novo genotyping of rs3801387 (in perfect linkage disequilibrium (LD) with rs917727) in 1,014 mothers of children from the discovery cohort. The top signal mapping in the surroundings of WNT16 was replicated across studies with a meta-analysis Pu200a=u200a2.6×10−31 and an effect size explaining between 0.6%–1.8% of TB-BMD variance. Conditional analyses on this signal revealed a secondary signal for total body BMD (Pu200a=u200a1.42×10−10) for rs4609139 and mapping to C7orf58. We also examined the genomic region for association with skull BMD to test if the associations were independent of skeletal loading. We identified two signals influencing skull BMD variation, including rs917727 (Pu200a=u200a1.9×10−16) and rs7801723 (Pu200a=u200a8.9×10−28), also mapping to C7orf58 (r2u200a=u200a0.50 with rs4609139). Wnt16 knockout (KO) mice with reduced total body BMD and gene expression profiles in human bone biopsies support a role of C7orf58 and WNT16 on the BMD phenotypes observed at the human population level. In summary, we detected two independent signals influencing total body and skull BMD variation in children and adults, thus demonstrating the presence of allelic heterogeneity at the WNT16 locus. One of the skull BMD signals mapping to C7orf58 is mostly driven by children, suggesting temporal determination on peak bone mass acquisition. Our life-course approach postulates that these genetic effects influencing peak bone mass accrual may impact the risk of osteoporosis later in life.

Genetic determinants of trabecular and cortical volumetric bone mineral densities and bone microstructure

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 (nu200a=u200a5,878) followed by replication (nu200a=u200a1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, pu200a=u200a3.6×10−14; LOC285735, rs271170, pu200a=u200a2.7×10−12; OPG, rs7839059, pu200a=u200a1.2×10−10; and ESR1/C6orf97, rs6909279, pu200a=u200a1.1×10−9). The trabecular vBMD GWA meta-analysis (nu200a=u200a2,500) followed by replication (nu200a=u200a1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, pu200a=u200a1.9×10−9). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (nu200a=u200a729). 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.

Eight common genetic variants associated with serum DHEAS levels suggest a key role in ageing mechanisms.

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands—yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; pu200a=u200a3.15×10−36), SULT2A1 (rs2637125; pu200a=u200a2.61×10−19), ARPC1A (rs740160; pu200a=u200a1.56×10−16), TRIM4 (rs17277546; pu200a=u200a4.50×10−11), BMF (rs7181230; pu200a=u200a5.44×10−11), HHEX (rs2497306; pu200a=u200a4.64×10−9), BCL2L11 (rs6738028; pu200a=u200a1.72×10−8), and CYP2C9 (rs2185570; pu200a=u200a2.29×10−8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS.

Genome wide association identifies common variants at the SERPINA6/SERPINA1 locus influencing plasma cortisol and corticosteroid binding globulin

Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30–60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

The growth hormone/insulin‐like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF‐related proteins including IGF‐I and IGF‐binding protein‐3 (IGFBP‐3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF‐I and IGFBP‐3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP‐3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF‐I and IGFBP‐3 concentrations. The IGF‐I‐decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity‐associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF‐I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF‐I‐ and IGFBP‐3‐associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF‐I and IGFBP‐3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity‐associated loci.

Limited Clinical Utility of a Genetic Risk Score for the Prediction of Fracture Risk in Elderly Subjects

It is important to identify the patients at highest risk of fractures. A recent large‐scale meta‐analysis identified 63 autosomal single‐nucleotide polymorphisms (SNPs) associated with bone mineral density (BMD), of which 16 were also associated with fracture risk. Based on these findings, two genetic risk scores (GRS63 and GRS16) were developed. Our aim was to determine the clinical usefulness of these GRSs for the prediction of BMD, BMD change, and fracture risk in elderly subjects. We studied two male (Osteoporotic Fractures in Men Study [MrOS] US, MrOS Sweden) and one female (Study of Osteoporotic Fractures [SOF]) large prospective cohorts of older subjects, looking at BMD, BMD change, and radiographically and/or medically confirmed incident fractures (8067 subjects, 2185 incident nonvertebral or vertebral fractures). GRS63 was associated with BMD (≅3% of the variation explained) but not with BMD change. Both GRS63 and GRS16 were associated with fractures. After BMD adjustment, the effect sizes for these associations were substantially reduced. Similar results were found using an unweighted GRS63 and an unweighted GRS16 compared with those found using the corresponding weighted risk scores. Only minor improvements in C‐statistics (AUC) for fractures were found when the GRSs were added to a base model (age, weight, and height), and no significant improvements in C‐statistics were found when they were added to a model further adjusted for BMD. Net reclassification improvements with the addition of the GRSs to a base model were modest and substantially attenuated in BMD‐adjusted models. GRS63 is associated with BMD, but not BMD change, suggesting that the genetic determinants of BMD differ from those of BMD change. When BMD is known, the clinical utility of the two GRSs for fracture prediction is limited in elderly subjects.

Does bone resorption stimulate periosteal expansion? A cross sectional analysis of β-C-telopeptides of type I collagen (CTX), genetic markers of the RANKL pathway, and periosteal circumference as measured by pQCT †

We hypothesized that bone resorption acts to increase bone strength through stimulation of periosteal expansion. Hence, we examined whether bone resorption, as reflected by serum β‐C‐telopeptides of type I collagen (CTX), is positively associated with periosteal circumference (PC), in contrast to inverse associations with parameters related to bone remodeling such as cortical bone mineral density (BMDC). CTX and mid‐tibial peripheral quantitative computed tomography (pQCT) scans were available in 1130 adolescents (mean age 15.5 years) from the Avon Longitudinal Study of Parents and Children (ALSPAC). Analyses were adjusted for age, gender, time of sampling, tanner stage, lean mass, fat mass, and height. CTX was positively related to PC (βu2009=u20090.19 [0.13, 0.24]) (coefficientu2009=u2009SD change per SD increase in CTX, 95% confidence interval)] but inversely associated with BMDC (βu2009=u2009–0.46 [–0.52,–0.40]) and cortical thickness [βu2009=u2009–0.11 (–0.18, –0.03)]. CTX was positively related to bone strength as reflected by the strength‐strain index (SSI) (βu2009=u20090.09 [0.03, 0.14]). To examine the causal nature of this relationship, we then analyzed whether single‐nucleotide polymorphisms (SNPs) within key osteoclast regulatory genes, known to reduce areal/cortical BMD, conversely increase PC. Fifteen such genetic variants within or proximal to genes encoding receptor activator of NF‐κB (RANK), RANK ligand (RANKL), and osteoprotegerin (OPG) were identified by literature search. Six of the 15 alleles that were inversely related to BMD were positively related to CTX (pu2009<u20090.05 cut‐off) (nu2009=u20092379). Subsequently, we performed a meta‐analysis of associations between these SNPs and PC in ALSPAC (nu2009=u20093382), Gothenburg Osteoporosis and Obesity Determinants (GOOD) (nu2009=u2009938), and the Young Finns Study (YFS) (nu2009=u20091558). Five of the 15 alleles that were inversely related to BMD were positively related to PC (pu2009<u20090.05 cut‐off). We conclude that despite having lower BMD, individuals with a genetic predisposition to higher bone resorption have greater bone size, suggesting that higher bone resorption is permissive for greater periosteal expansion.