Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region.

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity. We then develop a novel extension for two-sample multivariable Mendelian randomization that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. Our empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes (T2D). Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than T2D liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritized brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. We hope the multivariable Mendelian randomization approach illustrated here is widely applicable to better understand mechanisms linking drug targets to diseases outcomes, and hence to guide drug development efforts.

Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin.

Microbiome studies of inflammatory bowel diseases (IBD) have achieved a scale for meta-analysis of dysbioses among populations. To enable microbial community meta-analyses generally, we develop MMUPHin for normalization, statistical meta-analysis, and population structure discovery using microbial taxonomic and functional profiles. Applying it to ten IBD cohorts, we identify consistent associations, including novel taxa such as Acinetobacter and Turicibacter, and additional exposure and interaction effects. A single gradient of dysbiosis severity is favored over discrete types to summarize IBD microbiome population structure. These results provide a benchmark for characterization of IBD and a framework for meta-analysis of any microbial communities.

Perinatal famine is associated with excess risk of proliferative retinopathy in patients with type 2 diabetes.

PURPOSE: Intrauterine undernutrition is associated with increased risk of type 2 diabetes. Children born premature or small for gestational age were reported to have abnormal retinal vascularization. However, whether intrauterine famine act as a trigger for diabetes complications, including retinopathy, is unknown. The aim of the current study was to evaluate long-term effects of perinatal famine on the risk of proliferative diabetic retinopathy (PDR). METHODS: We studied the risk for PDR among type 2 diabetes patients exposed to perinatal famine in two independent cohorts: the Ukrainian National Diabetes Registry (UNDR) and the Hong Kong Diabetes Registry (HKDR). We analysed individuals born during the Great Famine (the Holodomor, 1932-1933) and the WWII (1941-1945) famine in 101 095 (3601 had PDR) UNDR participants. Among 3021 (251 had PDR) HKDR participants, we studied type 2 diabetes patients exposed to perinatal famine during the WWII Japanese invasion in 1942-1945. RESULTS: During the Holodomor and WWII, perinatal famine was associated with a 1.76-fold (p = 0.019) and 3.02-fold (p = 0.001) increased risk of severe PDR in the UNDR. The risk for PDR was 1.66-fold elevated among individuals born in 1942 in the HKDR (p < 0.05). The associations between perinatal famine and PDR remained statistically significant after corrections for HbA1c in available 18 507 UNDR (padditive interaction < 0.001) and in 3021 HKDR type 2 diabetes patients (p < 0.05). CONCLUSION: In conclusion, type 2 diabetes patients, exposed to perinatal famine, have increased risk of PDR compared to those without perinatal famine exposure. Further studies are needed to understand the underlying mechanisms and to extend this finding to other diabetes complications.

Cholesterol Metabolism by Uncultured Human Gut Bacteria Influences Host Cholesterol Level.

The human microbiome encodes extensive metabolic capabilities, but our understanding of the mechanisms linking gut microbes to human metabolism remains limited. Here, we focus on the conversion of cholesterol to the poorly absorbed sterol coprostanol by the gut microbiota to develop a framework for the identification of functional enzymes and microbes. By integrating paired metagenomics and metabolomics data from existing cohorts with biochemical knowledge and experimentation, we predict and validate a group of microbial cholesterol dehydrogenases that contribute to coprostanol formation. These enzymes are encoded by ismA genes in a clade of uncultured microorganisms, which are prevalent in geographically diverse human cohorts. Individuals harboring coprostanol-forming microbes have significantly lower fecal cholesterol levels and lower serum total cholesterol with effects comparable to those attributed to variations in lipid homeostasis genes. Thus, cholesterol metabolism by these microbes may play important roles in reducing intestinal and serum cholesterol concentrations, directly impacting human health.

Genome-wide analysis of dental caries and periodontitis combining clinical and self-reported data.

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health.

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases.

Inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, affect several million individuals worldwide. Crohn's disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study's infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi'omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases.

Protocols, Methods, and Tools for Genome-Wide Association Studies (GWAS) of Dental Traits.

Oral health and disease are known to be influenced by complex interactions between environmental (e.g., social and behavioral) factors and innate susceptibility. Although the exact contribution of genomics and other layers of "omics" to oral health is an area of active research, it is well established that the susceptibility to dental caries, periodontal disease, and other oral and craniofacial traits is substantially influenced by the human genome. A comprehensive understanding of these genomic factors is necessary for the realization of precision medicine in the oral health domain. To aid in this direction, the advent and increasing affordability of high-throughput genotyping has enabled the simultaneous interrogation of millions of genetic polymorphisms for association with oral and craniofacial traits. Specifically, genome-wide association studies (GWAS) of dental caries and periodontal disease have provided initial insights into novel loci and biological processes plausibly implicated in these two common, complex, biofilm-mediated diseases. This paper presents a summary of protocols, methods, tools, and pipelines for the conduct of GWAS of dental caries, periodontal disease, and related traits. The protocol begins with the consideration of different traits for both diseases and outlines procedures for genotyping, quality control, adjustment for population stratification, heritability and association analyses, annotation, reporting, and interpretation. Methods and tools available for GWAS are being constantly updated and improved; with this in mind, the presented approaches have been successfully applied in numerous GWAS and meta-analyses among tens of thousands of individuals, including dental traits such as dental caries and periodontal disease. As such, they can serve as a guide or template for future genomic investigations of these and other traits.

The Supragingival Biofilm in Early Childhood Caries: Clinical and Laboratory Protocols and Bioinformatics Pipelines Supporting Metagenomics, Metatranscriptomics, and Metabolomics Studies of the Oral Microbiome.

Early childhood caries (ECC) is a biofilm-mediated disease. Social, environmental, and behavioral determinants as well as innate susceptibility are major influences on its incidence; however, from a pathogenetic standpoint, the disease is defined and driven by oral dysbiosis. In other words, the disease occurs when the natural equilibrium between the host and its oral microbiome shifts toward states that promote demineralization at the biofilm-tooth surface interface. Thus, a comprehensive understanding of dental caries as a disease requires the characterization of both the composition and the function or metabolic activity of the supragingival biofilm according to well-defined clinical statuses. However, taxonomic and functional information of the supragingival biofilm is rarely available in clinical cohorts, and its collection presents unique challenges among very young children. This paper presents a protocol and pipelines available for the conduct of supragingival biofilm microbiome studies among children in the primary dentition, that has been designed in the context of a large-scale population-based genetic epidemiologic study of ECC. The protocol is being developed for the collection of two supragingival biofilm samples from the maxillary primary dentition, enabling downstream taxonomic (e.g., metagenomics) and functional (e.g., transcriptomics and metabolomics) analyses. The protocol is being implemented in the assembly of a pediatric precision medicine cohort comprising over 6000 participants to date, contributing social, environmental, behavioral, clinical, and biological data informing ECC and other oral health outcomes.

A fully adjusted two-stage procedure for rank-normalization in genetic association studies.

When testing genotype-phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. Because genotypes are expected to have small effects (if any) investigators now routinely use a two-stage method, in which they first regress the trait on covariates, obtain residuals, rank-normalize them, and then use the rank-normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice, no further adjustment is done in the second stage. Here, we show that this widely used approach can lead to tests with undesirable statistical properties, due to both combination of a mis-specified mean-variance relationship and remaining covariate associations between the rank-normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome-wide and whole-genome sequencing association studies. We further propose and evaluate an alternative fully adjusted two-stage approach that adjusts for covariates both when residuals are obtained and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.

Consortium-based genome-wide meta-analysis for childhood dental caries traits.

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5-18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P 4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low [h2 of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h2 of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure.

Tooth loss is a complex measure of oral disease: Determinants and methodological considerations.

OBJECTIVES: Counts of missing teeth or measures of incident tooth loss are gaining attention as a simple way to measure dental status in large population studies. We explore the meaning of these metrics and how missing teeth might influence other measures of dental status. METHODS: An observational study was performed in 2 contrasting adult populations. In total, 62 522 adult participants were available with clinically assessed caries and periodontal indices from the Swedish arm of the Gene-Lifestyle Interactions and Dental Endpoints Study (GLIDE) and the Korea National Health and Nutrition Examination Survey (KNHANES) in the Republic of Korea. Longitudinal measures of tooth loss were available for 28 244 participants in GLIDE with median follow-up of 10.6 years. RESULTS: In longitudinal analysis, hazard for tooth loss was associated with baseline dental status (previous tooth loss, periodontal status and caries status) and socio-demographic variables (age, smoking status and highest educational level). Analysis of cross-sectional data suggested that indices of caries exposure were not independent of periodontal status. The strength and direction of association varied between groups, even for measures specifically intended to avoid measuring tooth loss. Individuals with impaired periodontal health (community periodontal index [CPI] 3 or higher in any sextant) had higher standardized decayed and filled surfaces (DFS; number of DFS divided by total number of tooth surfaces) in GLIDE (incidence risk ratio [IRR] 1.05 [95% CI: 1.04, 1.07], but lower standardized DFS in KNHANES (IRR: 0.95 [0.92, 0.98]) than individuals with better periodontal health (CPI <3 in all sextants). CONCLUSIONS: Incident tooth loss is a complex measure of dental disease, with multiple determinants. The relative importance of dental caries and periodontal disease as drivers of tooth loss differs between age groups. Measures of dental caries exposure are associated with periodontal status in the studied populations, and these associations can be population-specific. Consideration of the study-specific properties of these metrics may be required for valid inference in large population studies.

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

Nonfermented milk and other dairy products: associations with all-cause mortality.

Background: A positive association between nonfermented milk intake and increased all-cause mortality was recently reported, but overall, the association between dairy intake and mortality is inconclusive.Objective: We studied associations between intake of dairy products and all-cause mortality with an emphasis on nonfermented milk and fat content.Design: A total of 103,256 adult participants (women: 51.0%) from Northern Sweden were included (7121 deaths; mean follow-up: 13.7 y). Associations between all-cause mortality and reported intakes of nonfermented milk (total or by fat content), fermented milk, cheese, and butter were tested with the use of Cox proportional hazards models that were adjusted for age, sex, body mass index, smoking status, education, energy intake, examination year, and physical activity. To circumvent confounding, Mendelian randomization was applied in a subsample via the lactase LCT-13910 C/T single nucleotide polymorphism that is associated with lactose tolerance and milk intake.Results: High consumers of nonfermented milk (≥2.5 times/d) had a 32% increased hazard (HR: 1.32; 95% CI: 1.18, 1.48) for all-cause mortality compared with that of subjects who consumed milk ≤1 time/wk. The corresponding value for butter was 11% (HR: 1.11; 95% CI: 1.07, 1.21). All nonfermented milk-fat types were independently associated with increased HRs, but compared with full-fat milk, HRs were lower in consumers of medium- and low-fat milk. Fermented milk intake (HR: 0.90; 95% CI: 0.86, 0.94) and cheese intake (HR: 0.93; 95% CI: 0.91, 0.96) were negatively associated with mortality. Results were slightly attenuated by lifestyle adjustments but were robust in sensitivity analyses. Mortality was not significantly associated with the LCT-13910 C/T genotype in the smaller subsample. The amount and type of milk intake was associated with lifestyle variables.Conclusions: In the present Swedish cohort study, intakes of nonfermented milk and butter are associated with higher all-cause mortality, and fermented milk and cheese intakes are associated with lower all-cause mortality. Residual confounding by lifestyle cannot be excluded, and Mendelian randomization needs to be examined in a larger sample.

Circulating copper and zinc levels and risk of hepatobiliary cancers in Europeans.

BACKGROUND: Copper and zinc are essential micronutrients and cofactors of many enzymatic reactions that may be involved in liver-cancer development. We aimed to assess pre-diagnostic circulating levels of copper, zinc and their ratio (Cu/Zn) in relation to hepatocellular carcinoma (HCC), intrahepatic bile duct (IHBD) and gall bladder and biliary tract (GBTC) cancers. METHODS: A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. Serum zinc and copper levels were measured in baseline blood samples by total reflection X-ray fluorescence in cancer cases (HCC n=106, IHDB n=34, GBTC n=96) and their matched controls (1:1). The Cu/Zn ratio, an indicator of the balance between the micronutrients, was computed. Multivariable adjusted odds ratios and 95% confidence intervals (OR; 95% CI) were used to estimate cancer risk. RESULTS: For HCC, the highest vs lowest tertile showed a strong inverse association for zinc (OR=0.36; 95% CI: 0.13-0.98, Ptrend=0.0123), but no association for copper (OR=1.06; 95% CI: 0.45-2.46, Ptrend=0.8878) in multivariable models. The calculated Cu/Zn ratio showed a positive association for HCC (OR=4.63; 95% CI: 1.41-15.27, Ptrend=0.0135). For IHBC and GBTC, no significant associations were observed. CONCLUSIONS: Zinc may have a role in preventing liver-cancer development, but this finding requires further investigation in other settings.

Novel genetic loci associated with long-term deterioration in blood lipid concentrations and coronary artery disease in European adults.

Background: Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids. Methods: Participants from the GLACIER Study (Nmax = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms; replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (ΔTC) and triglycerides (ΔTG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; Nmax = 8263 participants) were used for replication. We conducted an in silico look-up for association with coronary artery disease (CAD) in the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAMplusC4D) Consortium (N ∼ 190 000) and functional annotation for the top ranking variants. Results: In total, 956 variants were associated (P < 0.01) with either ΔTC or ΔTG in GLACIER. In GLACIER, chr19:50121999 at APOE was associated with ΔTG and multiple SNPs in the APOA1/A4/C3/A5 region at genome-wide significance (P < 5 × 10-8), whereas variants in four loci, DOCK7, BRE, SYNE1 and KCNIP1, reached study-wide significance (P < 1.7 × 10-6). The rs7412 variant at APOE was associated with ΔTC in GLACIER (P < 1.7 × 10-6). In pooled analyses of all cohorts, 139 SNPs at six and five loci were associated with ΔTC and for ΔTG, respectively (P < 10-3). Of these, a variant at CAPN3 (P = 1.2 × 10-4), multiple variants at HPR (Pmin = 1.5 × 10-6) and a variant at SIX5 (P = 1.9 × 10-4) showed evidence for association with CAD. Conclusions: We identified seven novel genomic regions associated with long-term changes in blood lipids, of which three also raise CAD risk.

Statistical power considerations in genotype-based recall randomized controlled trials.

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for gene-metformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design.

The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk.

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.

Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference.

Sixty genetic loci associated with abdominal obesity, measured by waist circumference (WC) and waist-hip ratio (WHR), have been previously identified, primarily from studies conducted in European-ancestry populations. We conducted a meta-analysis of associations of abdominal obesity with approximately 2.5 million single nucleotide polymorphisms (SNPs) among 53,052 (for WC) and 48,312 (for WHR) individuals of Asian descent, and replicated 33 selected SNPs among 3,762 to 17,110 additional individuals. We identified four novel loci near the EFEMP1, ADAMTSL3 , CNPY2, and GNAS genes that were associated with WC after adjustment for body mass index (BMI); two loci near the NID2 and HLA-DRB5 genes associated with WHR after adjustment for BMI, and three loci near the CEP120, TSC22D2, and SLC22A2 genes associated with WC without adjustment for BMI. Functional enrichment analyses revealed enrichment of corticotropin-releasing hormone signaling, GNRH signaling, and/or CDK5 signaling pathways for those newly-identified loci. Our study provides additional insight on genetic contribution to abdominal obesity.

Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium.

BACKGROUND: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). METHODS: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49,066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17,672/31,394 with/without periodontitis); 68,761 participants with BMI and genotype data; and 57,871 participants (18,881/38,990 with/without periodontitis) with data on BMI and periodontitis. RESULTS: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. CONCLUSIONS: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals.