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Heme oxygenase 1 is a key enzyme in the management of heme in humans. A GT(n) repeat length in the heme oxygenase 1 gene (HMOX1) has been widely associated with a variety of phenotypes, including susceptibility to and outcomes in diabetes, cancer, infections, and neonatal jaundice. However, studies have generally been small and results inconsistent. In this study, we imputed the GT(n) repeat length in participants from 2 UK cohort studies (the UK Biobank study (n  = 463,005; recruited in 2006–2010) and the Avon Longitudinal Study of Parents and Children (ALSPAC; n  = 937; recruited in 1990–1991)), with the reliability of imputation tested in other cohorts (1000 Genomes Project, Human Genome Diversity Project, and Personal Genome Project UK). Subsequently, we measured the relationship between repeat length and previously identified associations (diabetes, chronic obstructive pulmonary disease, pneumonia, and infection-related mortality in the UK Biobank; neonatal jaundice in ALSPAC) and performed a phenomewide association study in the UK Biobank. Despite high-quality imputation (correlation between true repeat length and imputed repeat length > 0.9 in test cohorts), clinical associations were not identified in either the phenomewide association study or specific association studies. These findings were robust to definitions of repeat length and sensitivity analyses. Despite multiple smaller studies identifying associations across a variety of clinical settings, we could not replicate or identify any relevant phenotypic associations with the HMOX1 GT(n) repeat. [ABSTRACT FROM AUTHOR]

BACKGROUND: Left ventricular mass (LVM) is an important predictor of cardiovascular risk. In adolescence, LVM is commonly indexed to height2.7, although some evidence suggests that this may not fully account for sex differences. METHODS: We investigated appropriate allometric scaling of LVM to height, total lean mass, and body surface area, in a UK birth cohort of 2039 healthy adolescents (17±1 years). Allometric relationships were determined by linear regression stratified by sex, following log transformation of x and y variables [log(y)=a+b×log(x)], b is the allometric exponent. RESULTS: Log (LVM) showed linear relationships with log(height) and log(lean mass). Biased estimates of slope resulted when the sexes were pooled. The exponents were lower than the conventional estimate of 2.7 for males (mean [95% CI]=1.66 [1.30–2.03]) and females (1.58 [1.27–1.90]). When LVM was indexed to lean mass, the exponent was 1.16 (1.05–1.26) for males and 1.07 (0.97–1.16) for females. When LVM was indexed to estimated body surface area, the exponent was 1.53 (1.40–1.66) for males and 1.34 (1.24–1.45) for females. CONCLUSIONS: Allometric exponents derived from pooled data, including men and women without adjustment for sex were biased, possibly due to sex differences in body composition. We suggest that when assessing LVM, clinicians should consider body size, body composition, sex, and age. Our observations may also have implications for the identification of young individuals with cardiac hypertrophy. [ABSTRACT FROM AUTHOR]

Background In conventional epidemiology confounding of the exposure of interest with lifestyle or socioeconomic factors, and reverse causation whereby disease status influences exposure rather than vice versa, may invalidate causal interpretations of observed associations. Conversely, genetic variants should not be related to the confounding factors that distort associations in conventional observational epidemiological studies. Furthermore, disease onset will not influence genotype. Therefore, it has been suggested that genetic variants that are known to be associated with a modifiable (nongenetic) risk factor can be used to help determine the causal effect of this modifiable risk factor on disease outcomes. This approach, mendelian randomization, is increasingly being applied within epidemiological studies. However, there is debate about the underlying premise that associations between genotypes and disease outcomes are not confounded by other risk factors. We examined the extent to which genetic variants, on the one hand, and nongenetic environmental exposures or phenotypic characteristics on the other, tend to be associated with each other, to assess the degree of confounding that would exist in conventional epidemiological studies compared with mendelian randomization studies. Methods and Findings We estimated pairwise correlations between nongenetic baseline variables and genetic variables in a cross-sectional study comparing the number of correlations that were statistically significant at the 5%, 1%, and 0.01% level (α = 0.05, 0.01, and 0.0001, respectively) with the number expected by chance if all variables were in fact uncorrelated, using a two-sided binomial exact test. We demonstrate that behavioural, socioeconomic, and physiological factors are strongly interrelated, with 45% of all possible pairwise associations between 96 nongenetic characteristics (n = 4,560 correlations) being significant at the p < 0.01 level (the ratio of observed to expected significant associations was 45; p-value for difference between observed and expected < 0.000001). Similar findings were observed for other levels of significance. In contrast, genetic variants showed no greater association with each other, or with the 96 behavioural, socioeconomic, and physiological factors, than would be expected by chance. Conclusions These data illustrate why observational studies have produced misleading claims regarding potentially causal factors for disease. The findings demonstrate the potential power of a methodology that utilizes genetic variants as indicators of exposure level when studying environmentally modifiable risk factors., Introduction Observational epidemiology has had notable successes, but also high-profile failures, in that it has identified many modifiable exposures apparently increasing or decreasing disease risk that have been revealed by [...]

Abstract Background Recent work has shown that population stratification can have confounding effects on genetic association studies and statistical methods have been developed to correct for these effects. Subsets of markers that are highly-differentiated between populations, ancestry-informative markers (AIMs), have been used to correct for population stratification. Often AIMs are discovered in one set of populations and then employed in a different set of populations. The underlying assumption in these cases is that the population under study has the same substructure as the population in which the AIMs were discovered. The present study assesses this assumption and evaluates the portability between worldwide populations of 10 SNPs found to be highly-differentiated within Britain (BritAIMs). Methods We genotyped 10 BritAIMs in ~1000 individuals from 53 populations worldwide. We assessed the degree to which these 10 BritAIMs capture population stratification in other groups of populations by use of the Fst statistic. We used Fst values from 2750 random markers typed in the same set of individuals as an empirical distribution to which the Fst values of the 10 BritAIMs were compared. Results Allele frequency differences between continental groups for the BritAIMs are not unusually high. This is also the case for comparisons within continental groups distantly related to Britain. However, two BritAIMs show high Fst between European populations and two BritAIMs show high Fst between populations from the Middle East. Overall the median Fst across all BritAIMs is not unusually high compared to the empirical distribution. Conclusion We find that BritAIMs are generally not useful to distinguish between continental groups or within continental groups distantly related to Britain. Moreover, our analyses suggest that the portability of AIMs across geographical scales (e.g. between Europe and Britain) can be limited and should therefore be taken into consideration in the design and interpretation of genetic association studies.

Abstract Background Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs). Methods We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals. Results On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations. Conclusion Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.

Recent advances in sequencing technology allow data on the human genome to be generated more quickly and in greater detail than ever before. Such detail includes findings that may be of significance to the health of the research participant involved. Although research studies generally do not feed back information on clinically significant findings (CSFs) to participants, this stance is increasingly being questioned. There may be difficulties and risks in feeding clinically significant information back to research participants, however, the UK10K consortium sought to address these by creating a detailed management pathway. This was not intended to create any obligation upon the researchers to feed back any CSFs they discovered. Instead, it provides a mechanism to ensure that any such findings can be passed on to the participant where appropriate. This paper describes this mechanism and the specific criteria, which must be fulfilled in order for a finding and participant to qualify for feedback. This mechanism could be used by future research consortia, and may also assist in the development of sound principles for dealing with CSFs. [ABSTRACT FROM AUTHOR]

Background Genome-wide association studies have revealed an association between several loci in the nicotinic acetylcholine receptor gene cluster CHRNA5-A3-B4 and daily cigarette consumption. Recent studies have sought to refine this phenotype, and have shown that a locus within this cluster, marked primarily by rs1051730 and rs16969968, is also associated with levels of cotinine, the primary metabolite of nicotine. This association remains after adjustment for self-reported smoking, which suggests that even amongst people who smoke the same number of cigarettes there is still genetically-influenced variation in nicotine consumption. This is likely to be due to differences in smoking topography, that is, how a cigarette is smoked (e.g., volume of smoke inhaled per puff, number of puffs taken per cigarette). The aim of this study is to determine potential mediation of the relationship between the rs1051730 locus and cotinine levels by smoking topography. Methods/design Adopting a recall-by-genotype design, we will recruit 200 adults from the Avon Longitudinal Study of Parents and Children on the basis of minor or major homozygote status at rs1051730 (100 in each genotype group). All participants will be current, daily smokers. Our primary study outcome measures will be measures of smoking topography: total volume of smoke (ml) inhaled per cigarette, total volume of smoke (ml) inhaled over of the course of one day, and salivary cotinine level (ng/ml). Discussion This study will extend our understanding of the biological basis of inter-individual variability in heaviness of smoking, and therefore in exposure to smoking-related toxins. The novel recall-by-genotype approach we will use is efficient, maximising statistical power, and enables the collection of extremely precise phenotypic data that are impractical to collect in a larger sample. The methods described within this protocol also hold the potential for wider application in the field of molecular genetics. [ABSTRACT FROM AUTHOR]

Lactase persistence is an autosomal-dominant trait that is common in European-derived populations. A basic tendency for lactase persistence to increase from the southeast to the northwest across European populations has been noted, but such trends within countries have not been extensively studied. We genotyped the C/T−13910 variant (rs4988235) that constitutes the putatively causal allele for lactase persistence (T allele representing persistence) in a general population sample of 3344 women aged 60–79 years from 23 towns across Britain. We found an overall frequency of 0.253 for the C (lactase non-persistence) allele, but with considerable gradients of decreasing frequency from the south to the north and from the east to the west of Britain for this allele. Daily sunlight was positively related to C (non-persistence) allele prevalence. However, sunlight exposure and latitude are strongly correlated, and it was not possible to identify which is the primary factor statistically underlying the distribution of lactase persistence. The C/T−13910 variant (rs4988235) was not related to drinking milk or bone health (although drinking milk itself was protective of bone health), and was essentially unrelated to a wide range of other lifestyle, health and demographic characteristics. One exception was general health being rated as being poor or fair, for which there was an odds ratio of 1.38 (1.04, 1.84) for women homozygous for the C allele; on adjustment for latitude and longitude of place of birth, this attenuated to 1.19 (0.87, 1.64). The lactase persistence variant could contribute to the examination of data for the existence of, and then statistical control for, population substructure in genetic association studies.European Journal of Human Genetics (2009) 17, 357–367; doi:10.1038/ejhg.2008.156; published online 17 September 2008 [ABSTRACT FROM AUTHOR]

Observational studies have contributed in a major way to understanding modifiable determinants of cardiovascular disease risk, but several examples exist of factors that were identified in observational studies as potentially protecting against coronary heart disease, that in randomized controlled trials had no such effect. The likely reason for misleading findings from observational epidemiological studies is that associations are influenced by confounding, bias, and reverse causation—where disease influences a risk factor, rather than vice versa. Mendelian randomization utilizes genetic variants that serve as proxy measures for modifiable risk factors to allow estimation of the causal influence of the modifiable risk factor in question. We present examples of the use of the Mendelian randomization approach and discuss both the limitations and potentials of this strategy. [ABSTRACT FROM AUTHOR]

Background: It is unclear whether C-reactive protein (CRP) is causally related to coronary heart disease (CHD). Genetic variants that are known to be associated with CRP levels can be used to provide causal inference of the effect of CRP on CHD. Our objective was to examine the association between CRP genetic variant +1444C.T (rs1130864) and CHD risk in the largest study to date of this association. Methods and Results: We estimated the association of CRP genetic variant +1444C.T (rs1130864) with CRP levels and with CHD in five studies and then pooled these analyses (N= 18,637 participants amongst whom there were 4,610 cases). CRP was associated with potential confounding factors (socioeconomic position, physical activity, smoking and body mass) whereas genotype (rs1130864) was not associated with these confounders. The pooled odds ratio of CHD per doubling of circulating CRP level after adjustment for age and sex was 1.13 (95%CI: 1.06, 1.21), and after further adjustment for confounding factors it was 1.07 (95%CI: 1.02, 1.13). Genotype (rs1130864) was associated with circulating CRP; the pooled ratio of geometric means of CRP level among individuals with the TT genotype compared to those with the CT/CC genotype was 1.21 (95%CI: 1.15, 1.28) and the pooled ratio of geometric means of CRP level per additional T allele was 1.14 (95%CI: 1.11, 1.18), with no strong evidence in either analyses of between study heterogeneity (I2 = 0%, p.0.9 for both analyses). There was no association of genotype (rs1130864) with CHD: pooled odds ratio 1.01 (95%CI: 0.88, 1.16) comparing individuals with TT genotype to those with CT/CC genotype and 0.96 (95%CI: 0.90, 1.03) per additional T allele (I2,7.5%, p.0.6 for both meta-analyses). An instrumental variables analysis (in which the proportion of CRP levels explained by rs1130864 was related to CHD) suggested that circulating CRP was not associated with CHD: the odds ratio for a doubling of CRP level was 1.04 (95%CI: 0.61, 1.80). Conclusions: We found no association of a genetic variant, which is known to be related to CRP levels, (rs1130864) and having CHD. These findings do not support a causal association between circulating CRP and CHD risk, but very large, extended, genetic association studies would be required to rule this out. [ABSTRACT FROM AUTHOR]

Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high-profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental variable (IV) approaches has been one approach to strengthening causal inferences in non-experimental situations. The use of germline genetic variants that proxy for environmentally modifiable exposures as instruments for these exposures is one form of IV analysis that can be implemented within observational epidemiological studies. The method has been referred to as 'Mendelian randomization', and can be considered as analogous to randomized controlled trials. This paper outlines Mendelian randomization, draws parallels with IV methods, provides examples of implementation of the approach and discusses limitations of the approach and some methods for dealing with these. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The author reflects on the risk of C-reactive protein (CRP) and cardiovascular disease. The author has stated that the role of CRP in cardiovascular disease risk has remained controversial. He has stated that higher circulating CRP levels are associated with coronary heart disease (CHD) incidence and mortality rates in prospective studies. The CRP levels are strongly related to many potential confounding factors that influence CHD incidence and mortality rates.

The analysis of individuals with ciliary chondrodysplasias can shed light on sensitive mechanisms controlling ciliogenesis and cell signalling that are essential to embryonic development and survival. Here we identify TCTEX1D2 mutations causing Jeune asphyxiating thoracic dystrophy with partially penetrant inheritance. Loss of TCTEX1D2 impairs retrograde intraflagellar transport (IFT) in humans and the protist Chlamydomonas, accompanied by destabilization of the retrograde IFT dynein motor. We thus define TCTEX1D2 as an integral component of the evolutionarily conserved retrograde IFT machinery. In complex with several IFT dynein light chains, it is required for correct vertebrate skeletal formation but may be functionally redundant under certain conditions.

Observational cohort studies can provide rich datasets with a diverse range of phenotypic variables. However, hypothesis-driven epidemiological analyses by definition only test particular hypotheses chosen by researchers. Furthermore, observational analyses may not provide robust evidence of causality, as they are susceptible to confounding, reverse causation and measurement error. Using body mass index (BMI) as an exemplar, we demonstrate a novel extension to the phenome-wide association study (pheWAS) approach, using automated screening with genotypic instruments to screen for causal associations amongst any number of phenotypic outcomes. We used a sample of 8,121 children from the ALSPAC dataset, and tested the linear association of a BMI-associated allele score with 172 phenotypic outcomes (with variable sample sizes). We also performed an instrumental variable analysis to estimate the causal effect of BMI on each phenotype. We found 21 of the 172 outcomes were associated with the allele score at an unadjusted p < 0.05 threshold, and use Bonferroni corrections, permutation testing and estimates of the false discovery rate to consider the strength of results given the number of tests performed. The most strongly associated outcomes included leptin, lipid profile, and blood pressure. We also found novel evidence of effects of BMI on a global self-worth score. [ABSTRACT FROM AUTHOR]

We investigated the role of common genetic variation in educational attainment and household income. We used data from 5,458 participants of the National Child Development Study to estimate: 1) the associations of rs9320913, rs11584700 and rs4851266 and socioeconomic position and educational phenotypes; and 2) the univariate chip-heritability of each phenotype, and the genetic correlation between each phenotype and educational attainment at age 16. The three SNPs were associated with most measures of educational attainment. Common genetic variation contributed to 6 of 14 socioeconomic background phenotypes, and 17 of 29 educational phenotypes. We found evidence of genetic correlations between educational attainment at age 16 and 4 of 14 social background and 8 of 28 educational phenotypes. This suggests common genetic variation contributes both to differences in educational attainment and its relationship with other phenotypes. However, we remain cautious that cryptic population structure, assortative mating, and dynastic effects may influence these associations. [ABSTRACT FROM AUTHOR]

Pubertal timing varies considerably and has been associated with a range of health outcomes in later life. To elucidate the underlying biological mechanisms, we performed multi-ancestry genetic analyses in ~800,000 women, identifying 1,080 independent signals associated with age at menarche. Collectively these loci explained 11% of the trait variance in an independent sample, with women at the top and bottom 1% of polygenic risk exhibiting a ~11 and ~14-fold higher risk of delayed and precocious pubertal development, respectively. These common variant analyses were supported by exome sequence analysis of ~220,000 women, identifying several genes, including rare loss of function variants in ZNF483 which abolished the impact of polygenic risk. Next, we implicated 660 genes in pubertal development using a combination of in silico variant-to-gene mapping approaches and integration with dynamic gene expression data from mouse embryonic GnRH neurons. This included an uncharacterized G-protein coupled receptor GPR83 , which we demonstrate amplifies signaling of MC3R , a key sensor of nutritional status. Finally, we identified several genes, including ovary-expressed genes involved in DNA damage response that co-localize with signals associated with menopause timing, leading us to hypothesize that the ovarian reserve might signal centrally to trigger puberty. Collectively these findings extend our understanding of the biological complexity of puberty timing and highlight body size dependent and independent mechanisms that potentially link reproductive timing to later life disease., Competing Interests: Competing interests J.R.B.P. and E.J.G. are employed by Adrestia Therapeutics. D.J.T. is employed by Genomics PLC. D.L.C. and J.P.B. are employed by GSK. E.T. is employed by Pfizer. D.A.L. has received support from Roche Disgnostics and Medtroic Ltd for work unrelated to the research in this paper. T.D.S. is co-founder and stakeholder of Zoe Global Ltd. P.A.F. conducts research funded by Amgen, Novartis and Pfizer, he received Honoraria from Roche, Novartis and Pfizer. M.W.B. conducts research funded by Amgen, Novartis and Pfizer.

Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10(-10) for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.

Early adversity predicts anxiety and depression but variation in response to adversity is not understood. We investigated whether association between early adversity and emotional symptoms in young children differs according to variation of the COMT gene. The main outcome measure was the emotionality subscale of the Strengths and Difficulties Questionnaire (SDQ) completed by mothers for 8,431 children aged 6-7 years old in the Avon Longitudinal Study of Parents and Children. Adversity measures included exposure to maternal postpartum depressive symptoms and adverse life events for children. DNA from the children was genotyped for five COMT polymorphisms including the COMT Val158Met locus. Maternal depression increased the odds of high emotionality in the children, (OR 1.99, 95% CI 1.73-2.29, P < 0.001) as did life events score, (OR 1.21 for each s.d. increase in life event score, 95% CI 1.15-1.27, P < 0.001). There was no main effect of Val158Met genotype on emotional symptoms (OR for effect of each copy of the methionine allele was 1.04, 95% CI 0.97-1.10, P = 0.284). The relationship between adversity and emotional symptoms did not vary by genotype (G x E for maternal depression chi(2) = 3.17, P = 0.205; G x E for life events chi(2) = 1.69, P = 0.430). There was no main effect of COMT haplotype, nor was there an interaction with adversity. Early adversity predicts emotional symptoms in children aged 6-7 years. Although some studies indicate a role for COMT in emotionality, anxiety, and depression in adults, no direct effect or interaction of COMT genotype was observed in this large sample of young children., (2008 Wiley-Liss, Inc.)

Networks of investigators have begun sharing best practices, tools and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be captured by online journals and through investigator networks. Systematic reviews will be expanded to include more meta-analyses of individual-level data and prospective meta-analyses. Field synopses will offer regularly updated overviews.

Background: C-reactive protein (CRP) has repeatedly been associated with blood pressure and prevalent and incident hypertension, but whether a causal link exists is uncertain., Methods and Results: We assessed the cross-sectional relations of CRP to systolic blood pressure, pulse pressure, and prevalent hypertension in a representative sample of >3500 British women aged 60 to 79 years. For both outcomes, substantial associations were observed. However, these associations were greatly attenuated by adjustment for a wide range of confounding factors acting over the life course. We further investigated causality using a Mendelian randomization approach by examining the association of the 1059G/C polymorphism in the human CRP gene with CRP and with blood pressure, pulse pressure, and hypertension. The polymorphism was associated with a robust difference in CRP, and the expectation would be for higher blood pressure and pulse pressure and greater prevalence of hypertension among those carrying the genetic variant associated with higher CRP levels. This was not observed, and the predicted causal effects of CRP on blood pressure, pulse pressure, and hypertension using instrumental variables methods were close to 0, although with wide CIs., Conclusions: CRP levels are associated with blood pressure, pulse pressure, and hypertension, but adjustment for life course confounding and a Mendelian randomization approach suggest the elevated CRP levels do not lead to elevated blood pressure.