Bone mass accrual during childhood and early adulthood is the most important modifiable determinant of lifelong skeletal health. Dental panoramic radiographs (DPRs) and measurements derived from them have yet to be assessed as a screening tool for low bone mineral density in children. Skull bone mineral density (SK-BMD) has high heritability and is less affected by environmental factors than measures of BMD at other skeletal sites. This study aimed to analyze the relationship between mandibular cortical thickness and SK-BMD in peripubertal children. This population-based cross-sectional study involved 2672 children aged 13 years from the Generation R Study. Mandibular cortical thickness was obtained from DPRs and quantified with the mental index (MI) and the superior panoramic mandibular index (sPMI). SK-BMD was quantified from total body dual-energy X-ray absorptiometry scans and weighted polygenic scores (wPGS). The determinants of mandibular cortical thickness were also assessed. The analysis was done with linear regression models, adjusted for confounders, and within a Mendelian randomization (MR) framework. Both MI and sPMI were significantly associated with SK-BMD in fully adjusted models. When the characteristics of the participants stratified for the extreme quintiles of the SK-BMD wPGS distribution were compared, only SK-BMD (p value < 0.001), sPMI (p value = 0.032), and MI (p value < 0.001) differed significantly between extremes. Mandibular cortical thickness parameters were significantly associated with SK-BMD in an unconfounded setting. DPRs may serve as a valuable tool for surmising low BMD in peripubertal children, once clinical cutoffs for mandibular cortical thickness are established.

Sarcopenia is a strong predictor of morbidity and mortality in older people, highlighting the need for effective prevention strategies. This study examined how different types of physical activity (PA) relate to sarcopenia and its components. We included 4849 participants (55.8

Previous evidence suggests that higher prepubertal adiposity protects against breast cancer risk. Whether this protection extends into early adulthood remains uncertain. We conducted genome-wide association studies on body mass index (BMI) in nulliparous women from menarche to <40 years across five cohorts, with additional analyses in three subintervals of this life stage. Results were meta-analyzed, and two-sample univariable and multivariable Mendelian randomization was applied within a lifecourse framework to assess the effect of BMI on breast cancer risk. Between menarche and <40 years, we observed heterogeneity in genetic effects. Genome-wide correlations further suggest that BMI during this early adult period may be partly influenced by distinct genetic factors compared with adiposity at other life stages. Higher genetically proxied BMI between menarche and 40 years reduced breast cancer risk. This protective effect attenuated after adjusting for prepubertal adiposity. These findings refine our understanding of adiposity's role in breast cancer and highlight earlier life stages as critical windows for risk modulation.

Background and aim:The metabolic roles in arterial calcification remain largely unclear. We aimed to elucidate the associations between nuclear magnetic resonance (NMR) metabolic biomarkers with site- and sex-specific arterial calcification as well as their causal nature. Methods:This study included participants from the Rotterdam Study (RS, N = 1062), Leiden Longevity Study (LLS, N = 272), and UK Biobank (UKBB, N = 271,793). In RS and LLS, we applied linear regression (both overall and sex-stratified) to assess the association between NMR metabolic biomarkers and arterial calcification at coronary artery (CAC), aortic arch (AAC), and aortic valve (AVC). Two-sample Mendelian randomization (MR) was employed using genome-wide association study of NMR biomarkers (N = 115,082) and CAC (N = 26,909) to infer their genetic causality. Biomarkers with consistent observational and causal associations were further examined for associations with coronary heart disease (CHD) in UKBB. Results:From multiple-testing correction (P-value < 4.39 × 10-4), three fatty acids ratio biomarkers were associated with decreased CAC burden: Omega_6_pct (Beta: -0.10, SE: 0.03, P-value: 2.94 × 10-4), PUFA_by_MUFA (Beta: -0.10, SE: 0.03, P-value: 3.08 × 10-4), and PUFA_pct (Beta: -0.10, SE: 0.03, P-value: 3.33 × 10-4). Sex-stratification revealed glycoprotein acetyls (GlycA) associated with CAC in males only (Beta: 0.13, SE: 0.04, P-value: 3.10 × 10-4). MR identified 17 biomarkers causally associated with CAC, 14 of which were subsequently associated with CHD in UKBB. Conclusions:We identified NMR-based metabolic biomarkers, particularly fatty acid ratios, that were significantly and causally associated with CAC burden. GlycA was associated with CAC in males only. Replication in UKBB further underscores their clinical relevance with CHD.

INTRODUCTION:Alcohol use is widely prevalent across different regions and cultural settings worldwide. While prior studies have suggested a positive impact of light alcohol consumption on bone mineral density (BMD), the relationship between different levels of alcohol consumption and BMD remains controversial. This study conducted cross-sectional analyses within the Rotterdam Study (RS) and UK Biobank (UKB) to examine this association, followed by one- and two-sample Mendelian randomization (MR) to assess potential causality. METHODS:This study included 4087 Europeans from the Rotterdam Study and 29,856 from the UK Biobank. In the cross-sectional analyses, multilinear regression was used to examine the association between alcohol consumption (g/day) and bone outcomes [i.e., bone mineral density (BMD) and trabecular bone score (TBS)]. For MR analyses, genetic variants associated with alcohol consumption and problematic alcohol use [defined as a combination of alcohol use disorders (AUD), alcohol dependence, and measures of Alcohol Use Disorders Identification Test-Problems (AUDIT-P)] were used as the instrumental variable (IV) for both exposures in both one- and two-sample MR. RESULTS:Cross-sectional analyses revealed a positive relationship between alcohol consumption and lumbar spine BMD (LS-BMD) (RS: β = 0.108, p = 0.009; UKB: β = 0.095, p = 6.87 × 10-13), femoral neck BMD (FN-BMD) (RS: β = 0.140, p = 0.001; UKB: β = 0.102, p = 3.42 × 10-15), and lumbar spine TBS (LS-TBS) (RS: β = 0.128, p = 0.004; UKB: β = 0.084, p = 6.53 × 10-07) in both studies, while alcohol consumption was only significantly associated with total body BMD (TB-BMD) (RS: β = 0.059, p = 0.087; UKB: β = 0.058, p = 7.48 × 10-9) in UKB. However, both one-sample and two-sample MR analyses found no evidence for a causal effect of genetically predicted alcohol consumption or problematic alcohol consumption on bone outcomes. CONCLUSION:In two independent studies, we observed a positive cross-sectional association of alcohol consumption with femoral neck BMD, lumbar spine BMD and TBS in European participants. However, MR findings did not demonstrate a causal link, suggesting that other factors or biases may confound the observed positive relationship. Further research is warranted to better understand the underlying mechanisms and potential confounders of this association.

BACKGROUND:Bones and muscles are connected chemically, anatomically, and functionally. While animal studies suggest the gut microbiome influences musculoskeletal aging, human evidence remains limited. We assessed associations between musculoskeletal phenotypes and gut microbiome composition in community-dwelling middle-aged and older adults. METHODS:We analyzed DXA-derived phenotypes from two population-based cohorts: the Rotterdam Study (mean age 62.7 years; n = 1249) and the Framingham Heart Study (mean age 55.2 years; n = 1227). Phenotypes included appendicular lean mass (ALM), femoral neck bone mineral density (FN-BMD), and trabecular bone score (TBS). Gut microbiome composition was assessed via 16S rRNA sequencing, and functional potential predicted using PICRUSt2. Multivariate linear regression analyses were adjusted for demographic, lifestyle, and clinical covariates. RESULTS:Alpha diversity was not associated with any musculoskeletal phenotype after multiple testing, whereas beta diversity was associated with ALM in the combined and female analyses. Four genera associated with ALM: lower abundance of Oscillibacter (β = -0.51, 95%CI [-0.74,-0.29]), Anaerotruncus (β = -0.41, 95%CI [-0.61,-0.21]), Eisenbergiella (β = -0.39, 95%CI [-0.59,-0.19]) and higher abundance of Agathobacter (β = 0.40, 95%CI [0.20,0.60]) were associated with higher ALM. In females, lower abundance of Anaerotruncus (β = -0.32, 95%CI [-0.45,-0.19]), Hungatella (β = -0.26, 95%CI [-0.38,-0.15]), and Clostridiales bacterium DTU089 (β = -0.37, 95%CI [-0.55,-0.19]), and higher biotin biosynthesis II pathway (β = 0.44, 95%CI [0.24,0.64]) associated with higher ALM. No robust associations were observed for bone traits. CONCLUSION:Although no associations were identified between gut microbial features and bone measures, several microbial genera were associated with appendicular lean mass in middle-aged and older adults, with evidence of sex-specific effects. Larger studies are needed to confirm these findings and clarify underlying mechanisms.

The widespread application of high-throughput Next Generation Sequencing (NGS) technologies has made microbiome research an emerging field in public health and biomedical sciences. However, there are still many challenges that need to be addressed in this field. Pipelines available to generate microbiome data across cohorts are diverse, and sources of variation to be recorded and evaluated during microbiome profiling have not been standardized. Moreover, meticulous quality control of the microbiome data processing, from collection to computational quantification is still challenging, especially in large population studies. Innovative approaches are required to handle samples and to minimize the potential bias introduced by logistic hurdles in biobanking. In this paper, we describe the methodological steps surrounding the optimization of the 16s rRNA gut microbiome profiling in two large prospective cohorts the Generation R Study (mean age 9.83 years, SD:0.32 years) and the Rotterdam Study (mean age 62.67,SD:5.66 years). This paper also highlights potential solutions to sample mislabeling in large-scale microbiome analysis. To summarize, our study addresses common problems in human microbiome research. It aims to improve the research quality and reliability by integrating more stringent quality control standards into microbiome research. ### Competing Interest Statement The authors have declared no competing interest.

Objective The objective of this study was to describe the microbial signature of the oral cavity of adolescents from the general population. We also aimed assess the impact of technical covariates related to sample collection and analysis on the microbiota data. Methods Within the Generation R Study, supragingival biofilm samples were collected at age 13 for microbiota profiling. Microbial data were obtained using 16S rRNA gene sequencing (V3–V4 region) and analysed at three levels: core microbiota composition, alpha diversity (Shannon, Chao1 index; linear regression), and beta diversity (weighted UniFrac distance; PERMANOVA). Results Participants (n = 4,645; 13.6 ± 0.38 years) shared a large core microbiota consisting of 23 different genera, with the five most abundant and prevalent—Streptococcus, Rothia, Haemophilus, Veillonella, and Neisseria—being well-known early colonizers of the dental biofilm. Among the technical covariates, sampling time was identified as the most impactful and showed a negative association with diversity (early-morning vs late-afternoon: Shannon; β:-0.54, 95%CI:-0.61;-0.46). Conclusion This study revealed a high similarity in oral microbiota of adolescents from the general population at the genus level, while highlighting the need to register and adjust studies for potential technical covariates. The characterization of oral microbiota in this study population provides a unique opportunity for future studies exploring the link between adolescents' oral microbiota and both oral and systemic health.

Background:Trabecular bone score (TBS) is a texture-based measurement derived from DXA scans, which describes the distribution of mineral across the vertebral bodies. Identifying its genetic determinants is crucial for enhancing understanding of its biological basis and clarifying its relationship with fracture risk. Methods:We conducted a large-scale genome-wide association study (GWAS) of TBS from 44,767 participants (95.08% European ancestry). Sex heterogeneity was assessed through sex-stratified GWAS. Post-GWAS analyses included functional annotation, gene-set enrichment analysis, and cis -expression quantitative trait locus ( cis- eQTL) colocalization. Two-sample and multivariable Mendelian randomization (MR) were employed to investigate the causal effect of TBS on fractures. Findings:We identified 33 independent variants associated with TBS, which explained 4.06% of TBS phenotypic variance. All the discovered signals map to previously identified BMD-associated loci. Additionally, we identified genetic variants in the RAB11FIP3 locus that exhibited a sex-heterogeneous effect, being associated with TBS exclusively in males. Functional annotation and colocalization identified functional genes related to TBS. The two-sample and multivariable MR analyses indicated that TBS potentially has an independent causal effect on fracture risk. Interpretation:Our study unveiled 33 independent loci associated with TBS, all in BMD-associated loci. One locus was further identified as associated with TBS only in males. MR results suggested that genetically derived TBS may be causally associated with fracture risk at different sites, potentially beyond BMD. This study provides insights into the TBS genetic architecture and uncovers its potential clinical applications in fracture risk prediction. Funding:All funding information can be found in the Acknowledgements section. Research in context:Evidence before this study: Osteoporosis is a common disease prevalent in older adults, mainly diagnosed by low bone mineral density and disruption of bone architecture. While the genetic determinants of bone mass have been well studied, the genetic architecture of bone features beyond BMD remains largely unknown.Added value of this study: This study presents a large genome-wide association meta-analysis of the trabecular bone score (TBS), a measurement of trabecular distribution of bone mineralization across vertebral bodies. Our study identified 33 independent variants associated with TBS and one association signal only in males. Functional annotation highlighted crucial genes related to TBS. The two-sample and multivariable Mendelian randomization (MR) analyses suggested that TBS may be causally linked with fracture risk, potentially independent of BMD.Implications of all the available evidence: Our study represents an expansion of the traditional bone density phenotype used in most previous skeletal genetic studies. Based on the findings that all of the significant loci for TBS have been previously identified in GWAS of BMD, we conclude that TBS-associated variants have pleiotropic effects affecting not only mineral density but also the distribution patterns of minerals in the cancellous bone. Continuing to perform genetic studies of new skeletal phenotypes beyond BMD could ultimately impact the management and prediction of osteoporosis patients.

Background and Aims:Recent evidence has implicated the gut microbiome in the regulation of host metabolites and the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD). However, the role of gut microbiome and its associated metabolites as regulators and/or modulators in MASLD remains understudied. We aimed to investigate the gut microbiome diversity and composition, its interaction with plasma metabolites, and MASLD risk using population-level data. Methods:We combined 16S rRNA sequencing of stool samples with a wide range of plasma metabolites measured by the Metabolon HD4 platform, and MASLD diagnosed by abdominal ultrasound in the Rotterdam Study cohort at baseline, between 2012 and 2014. We assessed the relationship of gut microbiome and metabolites with MASLD separately. Then, the metabolic profile as exposure was obtained through multivariate linear or logistic regression models for MASLD, liver fibrosis, alpha diversity, and MASLD-associated genera. Results:Our gut microbiome analysis showed that alpha diversity was lower in MASLD individuals (Shannon: P value = 2.06 × 10-6), beta diversity differed across MASLD strata (R2 = 0.00158, P value <.001), and Lachnospiraceae UCG-010 (odds ratio = 1.14 (1.06-1.23), area under the curve = 0.7807)) was significantly associated with MASLD, after multiple testing correction (q value<0.05). The metabolomics analysis showed 160 out of the 991 studied metabolites to be significantly associated with MASLD (q value<0.05). Moreover, 57 of the identified metabolites were significantly correlated with gut microbiome at the genus level in individuals with MASLD. Conclusion:This study indicates alterations in several plasma metabolites to be linked to gut microbiome in MASLD. These results lay the ground for future studies to better understand the host-gut microbiota metabolic interactions in the development of MASLD.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Parental genetic variants can indirectly influence the traits of their child through the environment, a concept termed 'genetic nurture', or indirect genetic effects (IGE). This study estimated the direct genetic effects (DGE), via direct allelic transmission, and IGE shaping height, body mass index (BMI), and bone mineral density (BMD) in a multi-ethnic Dutch pediatric cohort, examining children with repeated measurements at ages six, nine, and thirteen. We imputed missing parental alleles from the phased haplotypes of 1 931 478 variants (MAF > 1%), utilizing snipar (single nucleotide imputation of parents). We constructed polygenic risk scores (PRSs) and jointly regressed the proband's trait on their own PRS, while controlling for the proband's maternal and paternal PRSs. A total of 4488 probands, with genetic data, underwent at least one of the three specified measurements. We found statistically significant DGE estimates for the three traits across ages six, nine and thirteen. For instance, 71%-77% of the BMI variance explained by the BMI-PRS can be attributed solely to the DGE. IGE estimates reached significance only for BMI measured at ages nine (Beta: 0.05, 95%CI: 0.01-0.09) and thirteen (Beta: 0.05, 95%CI: 0.01-0.09). Maternal and paternal IGE were of a similar magnitude in all our analyses. Our findings indicate that genetic nurture has limited influence on anthropometric traits during formative years. In addition, we do not observe differences between the maternal and paternal indirect contributions to these traits, opposite to the stronger maternal nurturing effect reported for other traits.

Background The human gut microbiome changes considerably over time. Previous studies have shown that gut microbiome profiles correlate with multiple metabolic traits. As disease development is likely a lifelong process, evidence gathered at different life stages would help gain a better understanding of this correlation. Therefore, we aim to investigate how the association of the gut microbiome and metabolic traits change over the lifespan. Methods We identified microbiome patterns (clusters) within two population-based cohorts at different life stages, i.e., pre-adolescents of the Generation R Study (mean age 9.8 years; n = 1488) and older adults of the Rotterdam Study (RS, mean age 62.7 years; n = 1265) using K-Means clustering, and surveyed for host metabolic phenotypes, lifestyles and other factors driving these patterns. Analyses were replicated in the Lifelines-DEEP Study (mean age 45.0 years; n = 1117). The association between microbiome clusters and host metabolic health was evaluated as well as the link between microbiome clusters and incident atherosclerotic cardiovascular disease (ASCVD) in RS during follow-up (median 6.5 years). Findings We identified two distinct microbiome clusters (U and H) within each study population presenting contrasting metabolic statuses. Cluster U was characterized by lower microbiome diversity, increased Streptococcus, Fusicatenibacter, and decreased Prevotella_9 and Christensenellaceae_R-7_group; wherein individuals showed higher fat percentage, triglycerides, use of medications, and lower socioeconomic status. Individuals in cluster U had increased odds (between 1.10 and 1.65) of being relatively metabolically unhealthy and presented a higher 5-year ASCVD risk (mean risk 0.059 +/- 0.071 vs 0.047 +/- 0.042, p < 0.001). Interpretation We provide evidence of a life-course relationship between gut microbiome profiles and metabolic health. Funding R.L is supported by European Union Horizon 2020 research and innovation program under Marie Sk & lstrok;o- dowska-Curie grant agreement No 860898 [FIDELIO]. Copyright (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for ‘actionable’ genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-of-function (LoF) variants cause a rare neurodevelopmental and (treatable) metabolic disorder in males. The combination of deep phenotyping data with functional and computational tests and with outcomes in population cohorts, enabled us to: (i) identify the genetic aetiology of divergent clinical phenotypes of MCT8 deficiency with genotype-phenotype relationships present across survival and 24 out of 32 disease features; (ii) demonstrate a mild phenocopy in ~400,000 individuals with common genetic variants in MCT8; (iii) assess therapeutic effectiveness, which did not differ among LoF-categories; (iv) advance structural insights in normal and mutated MCT8 by delineating seven critical functional domains; (v) create a pathogenicity-severity MCT8 variant classifier that accurately predicted pathogenicity (AUC:0.91) and severity (AUC:0.86) for 8151 variants. Our information-dense mapping provides a generalizable approach to advance multiple dimensions of rare genetic disorders.

Background:Environmental factors play a role in the pathogenesis of complex traits including atopic eczema (AE) and a greater understanding of gene-environment interactions (G*E) is needed to define pathomechanisms for disease prevention. We analysed data from 16 European studies to test for interaction between the 24 most significant AE-associated loci identified from genome-wide association studies and 18 early-life environmental factors. We tested for replication using a further 10 studies and in vitro modelling to independently assess findings. Results:The discovery analysis showed suggestive evidence for interaction (p<0.05) between 7 environmental factors (antibiotic use, cat ownership, dog ownership, breastfeeding, elder sibling, smoking and washing practices) and at least one established variant for AE, 14 interactions in total (maxN=25,339). In replication analysis (maxN=252,040) dog exposure*rs10214237 (on chromosome 5p13.2 near IL7R) was nominally significant (ORinteraction=0.91 [0.83-0.99] P=0.025), with a risk effect of the T allele observed only in those not exposed to dogs. A similar interaction with rs10214237 was observed for siblings in the discovery analysis (ORinteraction=0.84[0.75-0.94] P=0.003), but replication analysis was under-powered ORinteraction=1.09[0.82-1.46]). Rs10214237 homozygous risk genotype is associated with lower IL-7R expression in human keratinocytes, and dog exposure modelled in vitro showed a differential response according to rs10214237 genotype. Conclusions:Interaction analysis and functional assessment provide evidence that early-life dog exposure may modify the genetic effect of rs10214237 on AE via IL7R, supporting observational epidemiology showing a protective effect for dog ownership. The lack of evidence for other G*E studied here implies that only weak effects are likely to occur.

ObjectivesThe panoramic mandibular index (PMI) and mental index (MI) assessed on dental panoramic radiographs (DPRs) have been postulated as useful for the assessment of adult bone health. However, their utility in children remains to be determined. Our objective was to establish genetic determinants of the PMI/MI and to evaluate the relationship between these indices and total body less-head bone mineral density (TBLH-BMD).MethodsThis study was embedded in the Generation R Study at a mean age of 13 years. BMD was obtained from dual-energy X-ray (DXA) scans, while radiomorphometric measurements of the mandibular bone were obtained from DPRs. Genome-wide association studies (GWAS) on PMI/MI were performed. The association between PMI/MI and BMD was assessed following a combined observational and genetic analysis using a polygenic risk score (PGS).ResultsThe PMI and MI GWAS identified an association signal (p = 2.53 x 10- 9) mapping to the ODF3/BET1L/RIC8A/SIRT3 locus, previously associated with BMD. Significant differences in PMI and MI were observed across the extremes of the TBLH-BMD PGS distribution. One standard deviation (SD) increase in measured TBLH-BMD was associated with 0.244 SD increase in PMI and 0.426 SD increase in MI.ConclusionsOur results suggest that PMI/MI and BMD share common biological pathways, and the former may be considered as relevant markers if screening for children with impaired bone health using DPRs.Clinical relevanceThis study demonstrates that mandibular indices measured from panoramic radiographs can help clinicians identify pediatric patients who may have reduced bone mineral density. Both traits share a shared genetic and the association is not due to confounding factors. These findings highlight the potential of panoramic radiography as a valuable tool in assessing pediatric skeletal health.

BACKGROUND:Multiple environmental and genetic factors play a role in the pathogenesis of atopic eczema (AE). We aimed to investigate gene-environment interactions (G × E) to improve understanding of the pathophysiology. METHODS:We analysed data from 16 European studies to test for interaction between the 24 most significant AE-associated loci identified from genome-wide association studies and 18 early-life environmental factors. We tested for replication using a further 10 studies and in vitro modeling to independently assess findings. RESULTS:The discovery analysis (including 25,339 individuals) showed suggestive evidence for interaction (p < 0.05) between seven environmental factors (antibiotic use, cat ownership, dog ownership, breastfeeding, elder sibling, smoking and washing practices) and at least one established variant for AE, 14 interactions in total. In the replication analysis (254,532 individuals) dog exposure × rs10214237 (on chromosome 5p13.2 near IL7R) was nominally significant (ORinteraction = 0.91 [0.83-0.99] p = 0.025), with a risk effect of the T allele observed only in those not exposed to dogs. A similar interaction with rs10214237 was observed for siblings in the discovery analysis (ORinteraction = 0.84 [0.75-0.94] p = 0.003), but replication analysis was under-powered (ORinteraction = 1.09 [0.82-1.46]). rs10214237 homozygous risk genotype is associated with lower IL-7R expression in human keratinocytes, and dog exposure modelled in vitro showed a differential response according to rs10214237 genotype. CONCLUSION:Interaction analysis and functional assessment provide preliminary evidence that early-life dog exposure may modify the genetic effect of rs10214237 on AE via IL7R, supporting observational epidemiology showing a protective effect for dog ownership. The lack of evidence for other G × E studied here implies only weak effects are likely to occur.

ObjectiveThis systematic review summarizes the current knowledge on the association between the oral microbiota and dental caries in adolescents.DesignAn electronic search was carried out across five databases. Studies were included if they conducted research on generally healthy adolescents, applied molecular-based microbiological analyses and assessed caries status. Data extraction was performed by two reviewers and the Newcastle-Ottawa Scale was applied for quality assessment.ResultsIn total, 3935 records were reviewed which resulted in a selection of 20 cross-sectional studies (published 2005-2022) with a sample size ranging from 11 to 614 participants including adolescents between 11 and 19 years. The studies analyzed saliva, dental biofilm or tongue swabs with Checkerboard DNA-DNA hybridization, (q)PCR or Next-Generation Sequencing methods. Prevotella denticola, Scardoviae Wiggsiae, Streptococcus sobrinus and Streptococcus mutans were the most frequently reported species presenting higher abundance in adolescents with caries. The majority of the studies reported that the microbial diversity was similar between participants with and without dental caries.ConclusionThis systematic review is the first that shows how the oral microbiota composition in adolescents appears to differ between those with and without dental caries, suggesting certain taxa may be associated with increased caries risk. However, there is a need to replicate and expand these findings in larger, longitudinal studies that also focus on caries severity and take adolescent-specific factors into account.

Observational studies have reported inconsistent associations between bone mineral density (BMD) and coronary artery calcification (CAC). We examined the observational association of BMD with CAC in 2 large population-based studies and evaluated the evidence for a potential causal relation between BMD and CAC using polygenic risk scores (PRS), 1- and 2-sample Mendelian randomization (MR) approaches. Our study populations comprised 1414 individuals (mean age 69.9 yr, 52.0% women) from the Rotterdam Study and 2233 individuals (mean age 56.5 yr, 50.9% women) from the Framingham Heart Study with complete information on CAC and BMD measurements at the total body (TB-), lumbar spine (LS-), and femoral neck (FN-). We used linear regression models to evaluate the observational association between BMD and CAC. Subsequently, we compared the mean CAC across PRSBMD quintile groups at different skeletal sites. In addition, we used the 2-stage least squares regression and the inverse variance weighted (IVW) model as primary methods for 1- and 2-sample MR to test evidence for a potentially causal association. We did not observe robust associations between measured BMD levels and CAC. These results were consistent with a uniform random distribution of mean CAC across PRSBMD quintile groups (P-value > .05). Moreover, neither 1- nor 2-sample MR supported the possible causal association between BMD and CAC. Our results do not support the contention that lower BMD is (causally) associated with an increased CAC risk. These findings suggest that previously reported epidemiological associations of BMD with CAC are likely explained by unmeasured confounders or shared etiology, rather than by causal pathways underlying both osteoporosis and vascular calcification processes.

Epidemiological evidence suggests existing comorbidity between postmenopausal osteoporosis (OP) and cardiovascular disease (CVD), but identification of possible shared genes is lacking. The skeletal global transcriptomes were analyzed in trans-iliac bone biopsies (n = 84) from clinically well-characterized postmenopausal women (50 to 86 years) without clinical CVD using microchips and RNA sequencing. One thousand transcripts highly correlated with areal bone mineral density (aBMD) were further analyzed using bioinformatics, and common genes overlapping with CVD and associated biological mechanisms, pathways and functions were identified. Fifty genes (45 mRNAs, 5 miRNAs) were discovered with established roles in oxidative stress, inflammatory response, endothelial function, fibrosis, dyslipidemia and osteoblastogenesis/calcification. These pleiotropic genes with possible CVD comorbidity functions were also present in transcriptomes of microvascular endothelial cells and cardiomyocytes and were differentially expressed between healthy and osteoporotic women with fragility fractures. The results were supported by a genetic pleiotropy-informed conditional False Discovery Rate approach identifying any overlap in single nucleotide polymorphisms (SNPs) within several genes encoding aBMD- and CVD-associated transcripts. The study provides transcriptional and genomic evidence for genes of importance for both BMD regulation and CVD risk in a large collection of postmenopausal bone biopsies. Most of the transcripts identified in the CVD risk categories have no previously recognized roles in OP pathogenesis and provide novel avenues for exploring the mechanistic basis for the biological association between CVD and OP.