Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

We initiate the Westlake BioBank for Chinese (WBBC) pilot project with 4,535 whole-genome sequencing (WGS) individuals and 5,841 high-density genotyping individuals, and identify 81.5 million SNPs and INDELs, of which 38.5% are absent in dbSNP Build 151. We provide a population-specific reference panel and an online imputation server (https://wbbc.westlake.edu.cn/) which could yield substantial improvement of imputation performance in Chinese population, especially for low-frequency and rare variants. By analyzing the singleton density of the WGS data, we find selection signatures in SNX29, DNAH1 and WDR1 genes, and the derived alleles of the alcohol metabolism genes (ADH1A and ADH1B) emerge around 7,000 years ago and tend to be more common from 4,000 years ago in East Asia. Genetic evidence supports the corresponding geographical boundaries of the Qinling-Huaihe Line and Nanling Mountains, which separate the Han Chinese into subgroups, and we reveal that North Han was more homogeneous than South Han.

Genome-wide association studies (GWASs) have identified numerous susceptibility loci for Parkinson’s disease (PD), but its genetic architecture remains underexplored in populations of non-European ancestry. To identify genetic variants associated with PD in the Chinese population, we performed a GWAS using whole-genome sequencing (WGS) in 1,972 cases and 2,478 controls, and a replication study in a total of 8209 cases and 9454 controls. We identified one new risk variant rs61204179 (P_combined = 1.47 × 10⁻⁹) with low allele frequency, four previously reported risk variants (NUCKS1/RAB29-rs11557080,SNCA-rs356182,FYN-rs997368, andVPS13C-rs2251086), as well as three risk variants inLRRK2coding region (A419V, R1628P, and G2385R) with genome-wide significance (P < 5 × 10⁻⁸) for PD in Chinese population. Moreover, of the reported genome-wide significant risk variants found mostly in European ancestry populations, the correlation coefficient (r_b) of effect size accounting for sampling errors was 0.91 between datasets and 63.6% attainedP < 0.05 in Chinese population. Accordingly, we estimated a heritability of 0.14–0.18 for PD, and a moderate genetic correlation between European ancestry and Chinese populations (r_g = 0.47, se = 0.21). Polygenic risk score (PRS) analysis revealed that individuals with PRS values in the highest quartile had a 3.9-fold higher risk of developing PD than the lowest quartile. In conclusion, the present GWAS identified PD-associated variants in Chinese population, as well as genetic factors shared among distant populations. Our findings shed light on the genetic homogeneity and heterogeneity of PD in different ethnic groups and suggested WGS might continue to improve our understanding of the genetic architecture of PD.

Objectives and methods With 432 513 samples from UK Biobank dataset, multivariable linear/logistic regression were used to estimate the relationship between psoriasis/psoriatic arthritis (PsA) and estimated bone mineral density (eBMD)/osteoporosis, controlling for potential confounders. Here, confounders were set in three ways: model0 (including age, height, weight, smoking and drinking), model1 (model0 +regular physical activity) and model2 (model1 +medication treatments). The eBMD was derived from heel ultrasound measurement. And 4904 patients with psoriasis and 847 patients with PsA were included in final analysis. Mendelian randomisation (MR) approach was used to evaluate the causal effect between them. Results Lower eBMD were observed in patients with PsA than in controls in both model0 (β-coefficient=−0.014, p=0.0006) and model1 (β-coefficient=−0.013, p=0.002); however, the association disappeared when conditioning on treatment with methotrexate or ciclosporin (model2) (β-coefficient=−0.005, p=0.28), mediation analysis showed that 63% of the intermediary effect on eBMD was mediated by medication treatment (p<2E-16). Patients with psoriasis without arthritis showed no difference of eBMD compared with controls. Similarly, the significance of higher risk of osteopenia in patients with PsA (OR=1.27, p=0.002 in model0) could be eliminated by conditioning on medication treatment (p=0.244 in model2). Psoriasis without arthritis was not related to osteopenia and osteoporosis. The weighted Genetic Risk Score analysis found that genetically determined psoriasis/PsA were not associated with eBMD (p=0.24 and p=0.88). Finally, MR analysis showed that psoriasis/PsA had no causal effect on eBMD, osteoporosis and fracture. Conclusions The effect of PsA on osteoporosis was secondary (eg, medication) but not causal. Under this hypothesis, psoriasis without arthritis was not a risk factor for osteoporosis.