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Abstract Limited whole genome sequencing (WGS) studies in Asian populations result in a lack of representative reference panels, thus hindering the discovery of ancestry-specific variants. Here, we present the South and East Asian reference Database (SEAD) panel ( https://imputationserver.westlake.edu.cn/ ), which integrates WGS data for 11,067 individuals from various sources across 17 Asian countries. The SEAD panel, comprising 22,134 haplotypes and 88,294,957 variants, demonstrates improved imputation accuracy for South Asian populations compared to 1000 Genomes Project, TOPMed, and ChinaMAP panels, with a higher proportion of well-imputed rare variants. For East Asian populations, SEAD shows concordance comparable to ChinaMAP, but outperforming TOPMed. Additionally, we apply the SEAD panel to conduct a genome-wide association study for total hip (Hip) and femoral neck (FN) bone mineral density (BMD) traits in 5369 genotyped Chinese samples. The single-variant test suggests that rare variants near SNTG1 are associated with Hip BMD (rs60103302, MAF = 0.0092, P = 1.67 × 10−7), and variant-set analysis further supports the association (P slide_window = 9.08 × 10−9, P gene_centric = 5.27 × 10−8). This association was not reported previously and can only be detected by using Asian reference panels. Preliminary in vitro experiments for one of the rare variants identified provide evidence that it upregulates SNTG1 expression, which could in turn inhibit the proliferation and differentiation of preosteoblasts.

Abstract Background Birth weight is considered not only to undermine future growth, but also to induce lifelong diseases; the aim of this study is to explore the relationship between birth weight and adult bone mass. Methods We performed multivariable regression analyses to assess the association of birth weight with bone parameters measured by dual-energy X-ray absorptiometry (DXA) and by quantitative ultrasound (QUS), independently. We also implemented a systemic Mendelian randomization (MR) analysis to explore the causal association between them with both fetal-specific and maternal-specific instrumental variables. Results In the observational analyses, we found that higher birth weight could increase the adult bone area (lumbar spine, β-coefficient= 0.17, P < 2.00 × 10−16; lateral spine, β-coefficient = 0.02, P = 0.04), decrease bone mineral content-adjusted bone area (BMCadjArea) (lumbar spine, β-coefficient= − 0.01, P = 2.27 × 10−14; lateral spine, β-coefficient = − 0.05, P = 0.001), and decrease adult bone mineral density (BMD) (lumbar spine, β-coefficient = − 0.04, P = 0.007; lateral spine; β-coefficient = − 0.03, P = 0.02; heel, β-coefficient = − 0.06, P < 2.00 × 10−16), and we observed that the effect of birth weight on bone size was larger than that on BMC. In MR analyses, the higher fetal-specific genetically determined birth weight was identified to be associated with higher bone area (lumbar spine; β-coefficient = 0.15, P = 1.26 × 10−6, total hip, β-coefficient = 0.15, P = 0.005; intertrochanteric area, β-coefficient = 0.13, P = 0.0009; trochanter area, β-coefficient = 0.11, P = 0.03) but lower BMD (lumbar spine, β-coefficient = − 0.10, P = 0.01; lateral spine, β-coefficient = − 0.12, P = 0.0003, and heel β-coefficient = − 0.11, P = 3.33 × 10−13). In addition, we found that the higher maternal-specific genetically determined offspring birth weight was associated with lower offspring adult heel BMD (β-coefficient = − 0.001, P = 0.04). Conclusions The observational analyses suggested that higher birth weight was associated with the increased adult bone area but decreased BMD. By leveraging the genetic instrumental variables with maternal- and fetal-specific effects on birth weight, the observed relationship could be reflected by both the direct fetal and indirect maternal genetic effects.

Summary: To infer the causality between obesity and fracture and the difference between general and abdominal obesity, a prospective study was performed in 456,921 participants, and 10,142 participants developed an incident fracture with follow-up period of 7.96 years. A U-shape relationship was observed between BMI and fracture, with the lowest risk of fracture in overweight participants. The obesity individuals had higher fracture risk when BMD was adjusted, and the protective effect of moderate-high BMI on fracture was mostly mediated by bone mineral density (BMD). However, for abdominal obesity, the higher WCadjBMI (linear) and HCadjBMI (J-shape) were found to be related to higher fracture risk, and less than 30% of the effect was mediated by BMD. By leveraging genetic instrumental variables, it provided additional evidences to support the aforementioned findings. In conclusion, keeping moderate-high BMI might be of benefit to old people in terms of fracture risk, whereas abdominal adiposity might increase risk of fracture.

Background: The obesity-hypertension pathogenesis is complex. From the phenotype to molecular mechanism, there is a long way to clarify the mechanism. To explore the association between obesity and hypertension, we correlate the phenotypes such as the waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), and diastolic blood pressure (DB) with the clinical laboratory data between four specific Chinese adult physical examination groups (newly diagnosed untreated just-obesity group, newly diagnosed untreated obesity-hypertension group, newly diagnosed untreated just-hypertension group, and normal healthy group), and the results may show something. Objective: To explore the mechanisms from obesity to hypertension by analyzing the correlations and differences between WC, BMI, SB, DB, and other clinical laboratory data indices in four specific Chinese adult physical examination groups. Methods: This cross-sectional study was conducted from September 2012 to July 2014, and 153 adult subjects, 34 women and 119 men, from 21 to 69 years, were taken from four characteristic Chinese adult physical examination groups (newly diagnosed untreated just-obesity group, newly diagnosed untreated obesity-hypertension group, newly diagnosed untreated just-hypertension group, and normal healthy group). The study was approved by the ethics committee of Hangzhou Center for Disease Control and Prevention. WC, BMI, SB, DB, and other clinical laboratory data were collected and analyzed by SPSS. Results: Serum levels of albumin (ALB)，alanine aminotransferase (ALT), low density lipoprotein cholesterol (LDLC), triglyceride (TG), high density lipoprotein cholesterol (HDLC), alkaline phosphatase (ALP), uric acid (Ua), and TC/HDLC (odds ratio) were statistically significantly different between the four groups. WC statistically significantly positively correlated with BMI, ALT, Ua, and serum levels of glucose (GLU), and TC/HDLC, and negatively with ALB, HDLC, and serum levels of conjugated bilirubin (CB). BMI was statistically significantly positively related to ALT, Ua, LDLC, WC, and TC/HDLC, and negatively to ALB, HDLC, and CB. DB statistically significantly positively correlated with ALP, BMI, and WC. SB was statistically significantly positively related to LDLC, GLU, serum levels of fructosamine (FA), serum levels of the total protein (TC), BMI, and WC. Conclusion: The negative body effects of obesity are comprehensive. Obesity may lead to hypertension through multiple ways by different percents. GGT, serum levels of gamma glutamyltransferase; ALB, serum levels of albumin; ALT, serum levels of alanine aminotransferase; LDLC, serum levels of low density lipoprotein cholesterol; TG, serum levels of triglyceride; HDLC, serum levels of high density lipoprotein cholesterol; FA, serum levels of fructosamine; S.C.R, serum levels of creatinine; IB, serum levels of indirect bilirubin; ALP, serum levels of alkaline phosphatase; CB, serum levels of conjugated bilirubin; UREA, Urea; Ua, serum levels of uric acid; GLU, serum levels of glucose; TC, serum levels of the total cholesterol; TB, serum levels of the total bilirubin; TP, serum levels of the total protein; TC/HDLC, TC/HDLC ratio.