Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent

BackgroundObservational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.MethodsWe applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases  =  46,325, controls  =  42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.ResultsIn the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m² increase, 95% confidence interval [CI]: 0.56–0.75, p = 3.32 × 10⁻¹⁰). The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31–0.62, p  =  9.91 × 10⁻⁸) and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46–0.71, p  =  1.88 × 10⁻⁸). This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60–0.84, p   =   1.64 × 10⁻⁷). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk.ConclusionsBMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.     

Early cartilage abnormalities at the hip are associated with obesity and body composition measures – a 3.0T MRI community-based study

IntroductionAlthough obesity is a risk factor for hip osteoarthritis (OA), the role of body composition, if any, is unclear. This study examines whether the body mass index (BMI) and body composition are associated with hip cartilage changes using magnetic resonance imaging (MRI) in community-based adults.Methods141 community-based participants with no clinical hip disease, including OA, had BMI and body composition (fat mass and fat free mass) measured at baseline (1990 to 1994), and BMI measured and 3.0 T MRI performed at follow-up (2009–2010). Femoral head cartilage volume was measured and femoral head cartilage defects were scored in the different hip regions.ResultsFor females, baseline BMI (β = −26 mm³, 95% Confidence interval (CI) -47 to −6 mm³, p = 0.01) and fat mass (β = −11 mm³, 95% CI −21 to −1 mm³, p = 0.03) were negatively associated with femoral head cartilage volume. Also, while increased baseline fat mass was associated with an increased risk of cartilage defects in the central superolateral region of the femoral head (Odds Ratio (OR) = 1.08, 95% CI 1.00–1.15, p = 0.04), increased baseline fat free mass was associated with a reduced risk of cartilage defects in this region (OR = 0.82, 95% CI 0.67–0.99; p = 0.04). For males, baseline fat free mass was associated with increased femoral head cartilage volume (β = 40 mm³, 95% CI 6 to 74 mm³, p = 0.02).ConclusionsIncreased fat mass was associated with adverse hip cartilage changes for females, while increased fat free mass was associated with beneficial cartilage changes for both genders. Further work is required to determine whether modifying body composition alters the development of hip OA.     

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

BackgroundEpidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.Methods and findingsWe selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10⁻⁸ from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m²; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10⁻⁵; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m², p = 2.1 × 10⁻⁵). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.ConclusionsIn this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

Aaron Leong and co-workers investigate causal risk factors for COVID-10 illness and severity.     

Genetic Association Analysis of Complex Diseases Incorporating Intermediate Phenotype Information

Genetic researchers often collect disease related quantitative traits in addition to disease status because they are interested in understanding the pathophysiology of disease processes. In genome-wide association (GWA) studies, these quantitative phenotypes may be relevant to disease development and serve as intermediate phenotypes or they could be behavioral or other risk factors that predict disease risk. Statistical tests combining both disease status and quantitative risk factors should be more powerful than case-control studies, as the former incorporates more information about the disease. In this paper, we proposed a modified inverse-variance weighted meta-analysis method to combine disease status and quantitative intermediate phenotype information. The simulation results showed that when an intermediate phenotype was available, the inverse-variance weighted method had more power than did a case-control study of complex diseases, especially in identifying susceptibility loci having minor effects. We further applied this modified meta-analysis to a study of imputed lung cancer genotypes with smoking data in 1154 cases and 1137 matched controls. The most significant SNPs came from the CHRNA3-CHRNA5-CHRNB4 region on chromosome 15q24–25.1, which has been replicated in many other studies. Our results confirm that this CHRNA region is associated with both lung cancer development and smoking behavior. We also detected three significant SNPs—rs1800469, rs1982072, and rs2241714—in the promoter region of the TGFB1 gene on chromosome 19 (p = 1.46×10⁻⁵, 1.18×10⁻⁵, and 6.57×10⁻⁶, respectively). The SNP rs1800469 is reported to be associated with chronic obstructive pulmonary disease and lung cancer in cigarette smokers. The present study is the first GWA study to replicate this result. Signals in the 3q26 region were also identified in the meta-analysis. We demonstrate the intermediate phenotype can potentially enhance the power of complex disease association analysis and the modified meta-analysis method is robust to incorporate intermediate phenotype or other quantitative risk factor in the analysis.     

Body mass index modulates the relationship of sugar-sweetened beverage intake with serum urate concentrations and gout

IntroductionBoth sugar-sweetened beverage (SSB) intake and body mass index (BMI) are associated with elevated serum urate concentrations and gout risk. The aim of this study was to determine whether the associations of SSB intake with serum urate and gout are moderated by BMI.MethodThe effects of chronic SSB intake on serum urate and gout status were analysed in a large cross-sectional population study. The effects of an acute fructose load on serum urate and fractional excretion of uric acid (FEUA) were examined over 180 minutes in a short-term intervention study. In all analyses, the responses were compared in those with BMI <25 mg/kg² (low BMI) and ≥25 mg/kg² (high BMI).ResultsIn the serum urate analysis (n = 12,870), chronic SSB intake was associated with increased serum urate in the high BMI group, but not in the low BMI group (P_difference = 3.6 × 10⁻³). In the gout analysis (n = 2578), chronic high SSB intake was associated with gout in the high BMI group, but not in the low BMI group (P_difference = 0.012). In the acute fructose loading study (n = 76), serum urate was increased in the high BMI group at baseline and throughout the observation period (P_{BMI group} <0.0001), but there were similar acute serum urate increases in both BMI groups in response to the fructose load (P_interaction = 0.99). The baseline FEUA was similar between the two BMI groups. However, following the fructose load, FEUA responses in the BMI groups differed (P_interaction <0.0001), with increased FEUA at 120 minutes and 180 minutes in the low BMI group and reduced FEUA at 60 minutes in the high BMI group.ConclusionsThese data suggest that BMI influences serum urate and gout risk in response to chronic SSB intake, and renal tubular uric acid handling in response to an acute fructose load. In addition to many other health benefits, avoidance of SSBs may be particularly important in those with overweight/obesity to prevent hyperuricaemia and reduce gout risk.

Trials registration

Australian Clinical Trials Registry ACTRN12610001036000. Registered 24 November 2010.     

Split-bolus computed tomography urography (CTU) achieves more than half of radiation dose reduction in females and overweight patients than conventional single-bolus computed tomography urography

ObjectiveTo compare radiation dose between single-bolus and split-bolus computed tomography urography (CTU).Materials and methodsWe prospectively enrolled patients undergoing single-bolus and split-bolus CTU from 2019 June to 2020 June. The age, sex and body mass index (BMI) of each patient was recorded and categorized into BMI classes. The radiation dose indices including volumetric computed dose index, size-specific dose estimate, dose length product and effective dose of each patient were compared between 2 CTU groups with calculation of dose reduction proportions (DRPs).ResultsSeventy-six patients underwent single-bolus (n = 39) and split-bolus (n = 37) CTU. Single-bolus CTU had higher radiation doses than split-bolus CTU and there were statistically significant differences of all radiation dose indices between two CTU groups without and with stratification by sex and BMI classes. The DRPs of volumetric computed dose index, size-specific dose estimate, dose length product and effective dose using split-bolus CTU were 49%, 49%. 50%, and 45%, respectively. Multiple linear regression with an effect size (f²) as 2.24 showed females (p = 0.027) and higher BMI classes (p = 2.38 *10⁻⁹) were associated with higher effective doses; and split-bolus CTU, lower effective doses (p = 5.40 *10⁻¹⁵). Using split-bolus CTU, females had consistently higher DRP of all radiation dose indices than males (54–55% versus 40–42%). Overweight patients had the largest DRP as 55% of effective dose.ConclusionsSplit-bolus CTU could be preferred by its significant radiation dose reduction effect in regard to single-bolus CTU, which was most profound in females and overweight patients.     

Integrative analysis of clinical and epigenetic biomarkers of mortality

DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome‐wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow‐up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry‐stratified meta‐analysis of all‐cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10⁻⁷, of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm‐based prediction models for all‐cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C‐index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, P _MR = 4.1 × 10⁻⁴) and negatively associated with longevity (Beta = −1.9, P _MR = 0.02). Pathway analysis revealed that genes associated with mortality‐related CpGs are enriched for immune‐ and cancer‐related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.     

Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits

The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI (p = 8.6 ×10⁻⁷), hip circumference (p = 3.4 × 10⁻⁸), and weight (p = 9.1 × 10⁻⁷). In Sardinia, homozygotes for the rare “G” allele of this SNP (minor allele frequency = 0.46) were 1.3 BMI units heavier than homozygotes for the common “A” allele. Within the PFKP gene, rs6602024 showed very strong association with BMI (p = 4.9 × 10⁻⁶). Homozygotes for the rare “A” allele of this SNP (minor allele frequency = 0.12) were 1.8 BMI units heavier than homozygotes for the common “G” allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans (N = 1,496) and in Hispanic Americans (N = 839), we replicated significant association between rs9930506 in the FTO gene and BMI (p-value for meta-analysis of European American and Hispanic American follow-up samples, p = 0.001), weight (p = 0.001), and hip circumference (p = 0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare “A” allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common “G” allele. In summary, we have completed a whole genome–association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population.     

Stratification by Smoking Status Reveals an Association of CHRNA5-A3-B4 Genotype with Body Mass Index in Never Smokers

We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00×10⁻¹⁰), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI +0.18 to +0.52, P = 6.38×10⁻⁵). An interaction test confirmed that these estimates differed from each other (P = 4.95×10⁻¹³). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.     

Genetic Variation in the 3'-Untranslated Region of NBN Gene Is Associated with Gastric Cancer Risk in a Chinese Population

NBN plays a crucial role in carcinogenesis as a core component for both homologous recombination (HR) and non-homologous end-joining (NHEJ) DNA double-strand breaks (DSBs) repair pathways. Genetic variants in the NBN gene have been associated with multiple cancers risk, suggesting pleiotropic effect on cancer. We hypothesized that genetic variants in the NBN gene may modify the risk of gastric cancer. To test this hypothesis, we evaluated the association between four potentially functional single nucleotide polymorphisms in NBN and gastric cancer risk in a case–control study of 1,140 gastric cancer cases and 1,547 controls in a Chinese population. We found that the A allele of rs10464867 (G>A) was significantly associated with a decreased risk of gastric cancer (odds ratio [OR] = 0.81, 95% confidence interval [95% CI] = 0.71–0.94; P = 4.71×10⁻³). Furthermore, the association between A allele of rs10464867 and decreased risk of gastric cancer was more significantly in elder individuals (per-allele OR = 0.72[0.59–0.88], P = 1.07×10⁻³), and male individuals (per-allele OR = 0.73[0.62–0.87], P = 3.68×10⁻⁴). We further conducted a haplotype analysis and identified that the NBN A_rs10464867G_rs14448G_rs1063053 haplotype conferred stronger protective effect on gastric cancer (OR = 0.76[0.65–0.89], P = 6.39×10⁻⁴). In summary, these findings indicate that genetic variants at NBN gene may contribute to gastric cancer susceptibility and may further advance our understanding of NBN gene in cancer development.     

Genome-Wide Association Study of Breast Cancer in the Japanese Population

Breast cancer is the most common malignancy among women in worldwide including Japan. Several studies have identified common genetic variants to be associated with the risk of breast cancer. Due to the complex linkage disequilibrium structure and various environmental exposures in different populations, it is essential to identify variants associated with breast cancer in each population, which subsequently facilitate the better understanding of mammary carcinogenesis. In this study, we conducted a genome-wide association study (GWAS) as well as whole-genome imputation with 2,642 cases and 2,099 unaffected female controls. We further examined 13 suggestive loci (P<1.0×10⁻⁵) using an independent sample set of 2,885 cases and 3,395 controls and successfully validated two previously-reported loci, rs2981578 (combined P-value of 1.31×10⁻¹², OR = 1.23; 95% CI = 1.16–.30) on chromosome 10q26 (FGFR2), rs3803662 (combined P-value of 2.79×10⁻¹¹, OR = 1.21; 95% CI = 1.15–.28) and rs12922061 (combined P-value of 3.97×10⁻¹⁰, OR = 1.23; 95% CI = 1.15–.31) on chromosome 16q12 (TOX3-LOC643714). Weighted genetic risk score on the basis of three significantly associated variants and two previously reported breast cancer associated loci in East Asian population revealed that individuals who carry the most risk alleles in category 5 have 2.2 times higher risk of developing breast cancer in the Japanese population than those who carry the least risk alleles in reference category 1. Although we could not identify additional loci associated with breast cancer, our study utilized one of the largest sample sizes reported to date, and provided genetic status that represent the Japanese population. Further local and international collaborative study is essential to identify additional genetic variants that could lead to a better, accurate prediction for breast cancer.     

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10⁻⁸, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10⁻⁸, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10⁻⁸, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10⁻⁴). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.     

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study

Background

Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR).

Methods and Findings

We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N _SNPs = 49), fasting glucose (N _SNPs = 36), insulin resistance (N _SNPs = 10), body mass index (BMI, N _SNPs = 32), total cholesterol (N _SNPs = 73), HDL-cholesterol (N _SNPs = 71), LDL-cholesterol (N _SNPs = 57), triglycerides (N _SNPs = 39), systolic blood pressure (SBP, N _SNPs = 24), smoking initiation (N _SNPs = 1), smoking quantity (N _SNPs = 3), university completion (N _SNPs = 2), and years of education (N _SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10⁻³). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10⁻⁸). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10⁻³), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses.

Conclusions

Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.     

Genome-wide Association Study Identifies Five Susceptibility Loci for Follicular Lymphoma outside the HLA Region

Genome-wide association studies (GWASs) of follicular lymphoma (FL) have previously identified human leukocyte antigen (HLA) gene variants. To identify additional FL susceptibility loci, we conducted a large-scale two-stage GWAS in 4,523 case subjects and 13,344 control subjects of European ancestry. Five non-HLA loci were associated with FL risk: 11q23.3 (rs4938573, p = 5.79 × 10⁻²⁰) near CXCR5; 11q24.3 (rs4937362, p = 6.76 × 10⁻¹¹) near ETS1; 3q28 (rs6444305, p = 1.10 × 10⁻¹⁰) in LPP; 18q21.33 (rs17749561, p = 8.28 × 10⁻¹⁰) near BCL2; and 8q24.21 (rs13254990, p = 1.06 × 10⁻⁸) near PVT1. In an analysis of the HLA region, we identified four linked HLA-DRβ1 multiallelic amino acids at positions 11, 13, 28, and 30 that were associated with FL risk (p_omnibus = 4.20 × 10⁻⁶⁷ to 2.67 × 10⁻⁷⁰). Additional independent signals included rs17203612 in HLA class II (odds ratio [OR_per-allele] = 1.44; p = 4.59 × 10⁻¹⁶) and rs3130437 in HLA class I (OR_per-allele = 1.23; p = 8.23 × 10⁻⁹). Our findings further expand the number of loci associated with FL and provide evidence that multiple common variants outside the HLA region make a significant contribution to FL risk.     

Physical Activity Attenuates the Genetic Predisposition to Obesity in 20,000 Men and Women from EPIC-Norfolk Prospective Population Study

Background

We have previously shown that multiple genetic loci identified by genome-wide association studies (GWAS) increase the susceptibility to obesity in a cumulative manner. It is, however, not known whether and to what extent this genetic susceptibility may be attenuated by a physically active lifestyle. We aimed to assess the influence of a physically active lifestyle on the genetic predisposition to obesity in a large population-based study.

Methods and Findings

We genotyped 12 SNPs in obesity-susceptibility loci in a population-based sample of 20,430 individuals (aged 39–79 y) from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with an average follow-up period of 3.6 y. A genetic predisposition score was calculated for each individual by adding the body mass index (BMI)-increasing alleles across the 12 SNPs. Physical activity was assessed using a self-administered questionnaire. Linear and logistic regression models were used to examine main effects of the genetic predisposition score and its interaction with physical activity on BMI/obesity risk and BMI change over time, assuming an additive effect for each additional BMI-increasing allele carried. Each additional BMI-increasing allele was associated with 0.154 (standard error [SE] 0.012) kg/m² (p = 6.73×10⁻³⁷) increase in BMI (equivalent to 445 g in body weight for a person 1.70 m tall). This association was significantly (p _interaction = 0.005) more pronounced in inactive people (0.205 [SE 0.024] kg/m² [p = 3.62×10⁻¹⁸; 592 g in weight]) than in active people (0.131 [SE 0.014] kg/m² [p = 7.97×10⁻²¹; 379 g in weight]). Similarly, each additional BMI-increasing allele increased the risk of obesity 1.116-fold (95% confidence interval [CI] 1.093–1.139, p = 3.37×10⁻²⁶) in the whole population, but significantly (p _interaction = 0.015) more in inactive individuals (odds ratio [OR] = 1.158 [95% CI 1.118–1.199; p = 1.93×10⁻¹⁶]) than in active individuals (OR = 1.095 (95% CI 1.068–1.123; p = 1.15×10⁻¹²]). Consistent with the cross-sectional observations, physical activity modified the association between the genetic predisposition score and change in BMI during follow-up (p _interaction = 0.028).

Conclusions

Our study shows that living a physically active lifestyle is associated with a 40% reduction in the genetic predisposition to common obesity, as estimated by the number of risk alleles carried for any of the 12 recently GWAS-identified loci. Please see later in the article for the Editors'' Summary     

Characterization of the major histocompatibility complex locus association with Beh?et’s disease in Iran

IntroductionThe aim of this study was to characterize the association of human leukocyte antigen (HLA) B alleles and major histocompatibility complex (MHC) single nucleotide polymorphisms (SNPs) with Behçet’s disease (BD) in an Iranian dataset.MethodsThe association of three SNPs in the MHC region previously identified as the most associated in high-density genotyping studies was tested in a case–control study on 973 BD patients and 825 controls from Iran, and the association of HLA-B alleles was tested in a subset of 681 patients and 414 controls.ResultsWe found that HLA-B*51 (P = 4.11 × 10⁻⁴¹, OR [95% CI] = 4.63[3.66-5.85]) and B*15 confer risk for BD (P = 2.83 × 10⁻², OR [95% CI] = 1.75[1.08-2.84]) in Iranian, and in B*51 negative individuals, only the B*15 allele is significantly associated with BD (P = 2.51 × 10⁻³, OR [95% CI] = 2.40[1.37-4.20]). rs76546355, formerly known as rs116799036, located between HLA-B and MICA (MHC class I polypeptide-related sequence A), demonstrated the same level of association with BD as HLA-B*51 (P_adj = 1.78 × 10⁻⁴⁶, OR [95% CI] = 5.46[4.21-7.09], and P_adj = 8.34 × 10⁻⁴⁸, OR [95% CI] = 5.44[4.20-7.05], respectively) in the HLA-B allelotyped subset, while rs2848713 was less associated (P_adj = 7.14 × 10⁻³⁵, OR [95% CI] = 3.73[2.97-4.69]) and rs9260997 was not associated (P_adj = 1.00 × 10⁻¹). Additionally, we found that B*51 genotype-phenotype correlations do not survive Bonferroni correction, while carriers of the rs76546355 risk allele predominate in BD cases with genital ulcers, positive pathergy test and positive BD family history (2.31 × 10⁻⁴ ≤ P ≤ 1.59 × 10⁻³).ConclusionsWe found that the HLA-B*51 allele and the rs76546355/rs116799036 MHC SNP are independent genetic risk factors for BD in Iranian, and that positivity for the rs76546355/rs116799036 risk allele, but not for B*51, does correlate with specific demographic characteristics or clinical manifestations in BD patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0585-6) contains supplementary material, which is available to authorized users.     

Genetic associations for two biological age measures point to distinct aging phenotypes

Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome‐wide association scans of two age‐adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinical biochemistry markers (Levine et al., 2018; Levine, 2013) in European‐descent participants from UK Biobank. The strongest signals were found in the APOE gene, tagged by the two major protein‐coding SNPs, PhenoAgeAccel—rs429358 (APOE e4 determinant) (p = 1.50 × 10⁻⁷²); BioAgeAccel—rs7412 (APOE e2 determinant) (p = 3.16 × 10⁻⁶⁰). Interestingly, we observed inverse APOE e2 and e4 associations and unique pathway enrichments when comparing the two biological age measures. Genes associated with BioAgeAccel were enriched in lipid related pathways, while genes associated with PhenoAgeAccel showed enrichment for immune system, cell function, and carbohydrate homeostasis pathways, suggesting the two measures capture different aging domains. Our study reaffirms that aging patterns are heterogeneous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition.     

Metabolic Signatures of Adiposity in Young Adults: Mendelian Randomization Analysis and Effects of Weight Change

Background

Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood.

Methods and Findings

We used Mendelian randomization to estimate causal effects of BMI on 82 metabolic measures in 12,664 adolescents and young adults from four population-based cohorts in Finland (mean age 26 y, range 16–39 y; 51% women; mean ± standard deviation BMI 24±4 kg/m²). Circulating metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. In cross-sectional analyses, elevated BMI was adversely associated with cardiometabolic risk markers throughout the systemic metabolite profile, including lipoprotein subclasses, fatty acid composition, amino acids, inflammatory markers, and various hormones (p<0.0005 for 68 measures). Metabolite associations with BMI were generally stronger for men than for women (median 136%, interquartile range 125%–183%). A gene score for predisposition to elevated BMI, composed of 32 established genetic correlates, was used as the instrument to assess causality. Causal effects of elevated BMI closely matched observational estimates (correspondence 87%±3%; R ² = 0.89), suggesting causative influences of adiposity on the levels of numerous metabolites (p<0.0005 for 24 measures), including lipoprotein lipid subclasses and particle size, branched-chain and aromatic amino acids, and inflammation-related glycoprotein acetyls. Causal analyses of certain metabolites and potential sex differences warrant stronger statistical power. Metabolite changes associated with change in BMI during 6 y of follow-up were examined for 1,488 individuals. Change in BMI was accompanied by widespread metabolite changes, which had an association pattern similar to that of the cross-sectional observations, yet with greater metabolic effects (correspondence 160%±2%; R ² = 0.92).

Conclusions

Mendelian randomization indicates causal adverse effects of increased adiposity with multiple cardiometabolic risk markers across the metabolite profile in adolescents and young adults within the non-obese weight range. Consistent with the causal influences of adiposity, weight changes were paralleled by extensive metabolic changes, suggesting a broadly modifiable systemic metabolite profile in early adulthood. Please see later in the article for the Editors'' Summary     

Association of Variants at UMOD with Chronic Kidney Disease and Kidney Stones—Role of Age and Comorbid Diseases

Chronic kidney disease (CKD) is a worldwide public health problem that is associated with substantial morbidity and mortality. To search for sequence variants that associate with CKD, we conducted a genome-wide association study (GWAS) that included a total of 3,203 Icelandic cases and 38,782 controls. We observed an association between CKD and a variant with 80% population frequency, rs4293393-T, positioned next to the UMOD gene (GeneID: 7369) on chromosome 16p12 (OR = 1.25, P = 4.1×10⁻¹⁰). This gene encodes uromodulin (Tamm-Horsfall protein), the most abundant protein in mammalian urine. The variant also associates significantly with serum creatinine concentration (SCr) in Icelandic subjects (N = 24,635, P = 1.3×10⁻²³) but not in a smaller set of healthy Dutch controls (N = 1,819, P = 0.39). Our findings validate the association between the UMOD variant and both CKD and SCr recently discovered in a large GWAS. In the Icelandic dataset, we demonstrate that the effect on SCr increases substantially with both age (P = 3.0×10⁻¹⁷) and number of comorbid diseases (P = 0.008). The association with CKD is also stronger in the older age groups. These results suggest that the UMOD variant may influence the adaptation of the kidney to age-related risk factors of kidney disease such as hypertension and diabetes. The variant also associates with serum urea (P = 1.0×10⁻⁶), uric acid (P = 0.0064), and suggestively with gout. In contrast to CKD, the UMOD variant confers protection against kidney stones when studied in 3,617 Icelandic and Dutch kidney stone cases and 43,201 controls (OR = 0.88, P = 5.7×10⁻⁵).