Abstract
Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic ...consequences and/or by the psychosocial impact of higher adiposity. We performed one- and two- sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression OR: 1.50, 95%CI: 1.15, 1.95 and lower well-being ß: −0.15, 95%CI: −0.26, −0.04. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being.
Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic ...factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI 1.15, 1.27, P = 3x10-12) and PER2 (1.09 odds of morningness, 95% CI 1.06, 1.12, P = 4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI 1.9, 3.2, P = 5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI 1.3, 2.7, P = 1.2x10-9; and 1.6 minutes per allele, 95% CI 1.1, 2.2, P = 7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10-5) and oversleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans.
Objective To determine whether height and body mass index (BMI) have a causal role in five measures of socioeconomic status. Design Mendelian randomisation study to test for causal effects of ...differences in stature and BMI on five measures of socioeconomic status. Mendelian randomisation exploits the fact that genotypes are randomly assigned at conception and thus not confounded by non-genetic factors. Setting UK Biobank. Participants 119 669 men and women of British ancestry, aged between 37 and 73 years. Main outcome measures Age completed full time education, degree level education, job class, annual household income, and Townsend deprivation index. Results In the UK Biobank study, shorter stature and higher BMI were observationally associated with several measures of lower socioeconomic status. The associations between shorter stature and lower socioeconomic status tended to be stronger in men, and the associations between higher BMI and lower socioeconomic status tended to be stronger in women. For example, a 1 standard deviation (SD) higher BMI was associated with a £210 (€276; $300; 95% confidence interval £84 to £420; P=6×10−3) lower annual household income in men and a £1890 (£1680 to £2100; P=6×10−15) lower annual household income in women. Genetic analysis provided evidence that these associations were partly causal. A genetically determined 1 SD (6.3 cm) taller stature caused a 0.06 (0.02 to 0.09) year older age of completing full time education (P=0.01), a 1.12 (1.07 to 1.18) times higher odds of working in a skilled profession (P=6×10−7), and a £1130 (£680 to £1580) higher annual household income (P=4×10−8). Associations were stronger in men. A genetically determined 1 SD higher BMI (4.6 kg/m2) caused a £2940 (£1680 to £4200; P=1×10−5) lower annual household income and a 0.10 (0.04 to 0.16) SD (P=0.001) higher level of deprivation in women only. Conclusions These data support evidence that height and BMI play an important partial role in determining several aspects of a person’s socioeconomic status, especially women’s BMI for income and deprivation and men’s height for education, income, and job class. These findings have important social and health implications, supporting evidence that overweight people, especially women, are at a disadvantage and that taller people, especially men, are at an advantage.
Using a nontargeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycemia in a large population-based cohort of ...2,204 females (115 type 2 diabetic T2D case subjects, 192 individuals with impaired fasting glucose IFG, and 1,897 control subjects) from TwinsUK. Forty-two metabolites from three major fuel sources (carbohydrates, lipids, and proteins) were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain keto-acid metabolite 3-methyl-2-oxovalerate was the strongest predictive biomarker for IFG after glucose (odds ratio OR 1.65 95% CI 1.39-1.95, P = 8.46 × 10(-9)) and was moderately heritable (h(2) = 0.20). The association was replicated in an independent population (n = 720, OR 1.68 1.34-2.11, P = 6.52 × 10(-6)) and validated in 189 twins with urine metabolomics taken at the same time as plasma (OR 1.87 1.27-2.75, P = 1 × 10(-3)). Results confirm an important role for catabolism of branched-chain amino acids in T2D and IFG. In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of nontargeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.
Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose ...and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.
Abstract
Background
Glycemic traits—such as hyperinsulinemia, hyperglycemia, and type 2 diabetes—have been associated with higher colorectal cancer risk in observational studies; however, causality ...of these associations is uncertain. We used Mendelian randomization (MR) to estimate the causal effects of fasting insulin, 2-hour glucose, fasting glucose, glycated hemoglobin (HbA1c), and type 2 diabetes with colorectal cancer.
Methods
Genome-wide association study summary data were used to identify genetic variants associated with circulating levels of fasting insulin (n = 34), 2-hour glucose (n = 13), fasting glucose (n = 70), HbA1c (n = 221), and type 2 diabetes (n = 268). Using 2-sample MR, we examined these variants in relation to colorectal cancer risk (48 214 case patient and 64 159 control patients).
Results
In inverse-variance models, higher fasting insulin levels increased colorectal cancer risk (odds ratio OR per 1-SD = 1.65, 95% confidence interval CI = 1.15 to 2.36). We found no evidence of any effect of 2-hour glucose (OR per 1-SD = 1.02, 95% CI = 0.86 to 1.21) or fasting glucose (OR per 1-SD = 1.04, 95% CI = 0.88 to 1.23) concentrations on colorectal cancer risk. Genetic liability to type 2 diabetes (OR per 1-unit increase in log odds = 1.04, 95% CI = 1.01 to 1.07) and higher HbA1c levels (OR per 1-SD = 1.09, 95% CI = 1.00 to 1.19) increased colorectal cancer risk, although these findings may have been biased by pleiotropy. Higher HbA1c concentrations increased rectal cancer risk in men (OR per 1-SD = 1.21, 95% CI = 1.05 to 1.40), but not in women.
Conclusions
Our results support a causal effect of higher fasting insulin, but not glucose traits or type 2 diabetes, on increased colorectal cancer risk. This suggests that pharmacological or lifestyle interventions that lower circulating insulin levels may be beneficial in preventing colorectal tumorigenesis.
Human DNA polymorphisms vary across geographic regions, with the most commonly observed variation reflecting distant ancestry differences. Here we investigate the geographic clustering of common ...genetic variants that influence complex traits in a sample of ~450,000 individuals from Great Britain. Of 33 traits analysed, 21 showed significant geographic clustering at the genetic level after controlling for ancestry, probably reflecting migration driven by socioeconomic status (SES). Alleles associated with educational attainment (EA) showed the most clustering, with EA-decreasing alleles clustering in lower SES areas such as coal mining areas. Individuals who leave coal mining areas carry more EA-increasing alleles on average than those in the rest of Great Britain. The level of geographic clustering is correlated with genetic associations between complex traits and regional measures of SES, health and cultural outcomes. Our results are consistent with the hypothesis that social stratification leaves visible marks in geographic arrangements of common allele frequencies and gene-environment correlations.
Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and ...psoriasis.
Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio OR = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied.
Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship.
Being a morning person is a behavioural indicator of a person's underlying circadian rhythm. Using genome-wide data from 697,828 UK Biobank and 23andMe participants we increase the number of genetic ...loci associated with being a morning person from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we find that the chronotype loci associate with sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 min earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans.
Frozen shoulder is a painful condition that often requires surgery and affects up to 5% of individuals aged 40-60 years. Little is known about the causes of the condition, but diabetes is a strong ...risk factor. To begin to understand the biological mechanisms involved, we aimed to identify genetic variants associated with frozen shoulder and to use Mendelian randomization to test the causal role of diabetes. We performed a genome-wide association study (GWAS) of frozen shoulder in the UK Biobank using data from 10,104 cases identified from inpatient, surgical and primary care codes. We used data from FinnGen for replication and meta-analysis. We used one-sample and two-sample Mendelian randomization approaches to test for a causal association of diabetes with frozen shoulder. We identified five genome-wide significant loci. The most significant locus (lead SNP rs28971325; OR = 1.20, 95% CI: 1.16-1.24, p = 5x10-29) contained WNT7B. This variant was also associated with Dupuytren's disease (OR = 2.31 2.24, 2.39, p<1x10-300) as were a further two of the frozen shoulder associated variants. The Mendelian randomization results provided evidence that type 1 diabetes is a causal risk factor for frozen shoulder (OR = 1.03 1.02-1.05, p = 3x10-6). There was no evidence that obesity was causally associated with frozen shoulder, suggesting that diabetes influences risk of the condition through glycemic rather than mechanical effects. We have identified genetic loci associated with frozen shoulder. There is a large overlap with Dupuytren's disease associated loci. Diabetes is a likely causal risk factor. Our results provide evidence of biological mechanisms involved in this common painful condition.
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