Transcriptome analysis reveals involvement of thiopurine S-methyltransferase in oxidation-reduction processes.

Thiopurine S-methyltransferase (TPMT) is an important enzyme involved in the deactivation of thiopurines and represents a major determinant of thiopurine-related toxicities. Despite its well-known importance in thiopurine metabolism, the understanding of its endogenous role is lacking. In the present study, we aimed to gain insight into the molecular processes involving TPMT by applying a data fusion approach to analyze whole-genome expression data. The RNA profiling was done on whole blood samples from 1017 adult male and female donors to the Estonian biobank using Illumina HTv3 arrays. Our results suggest that TPMT is closely related to genes involved in oxidoreductive processes. The in vitro experiments on different cell models confirmed that TPMT influences redox capacity of the cell by altering S-adenosylmethionine (SAM) consumption and consequently glutathione (GSH) synthesis. Furthermore, by comparing gene networks of subgroups of individuals, we identified genes, which could have a role in regulating TPMT activity. The biological relevance of identified genes and pathways will have to be further evaluated in molecular studies.

Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality.

BACKGROUND: Five modifiable risk factors are associated with cardiovascular disease and death from any cause. Studies using individual-level data to evaluate the regional and sex-specific prevalence of the risk factors and their effect on these outcomes are lacking. METHODS: We pooled and harmonized individual-level data from 112 cohort studies conducted in 34 countries and 8 geographic regions participating in the Global Cardiovascular Risk Consortium. We examined associations between the risk factors (body-mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, current smoking, and diabetes) and incident cardiovascular disease and death from any cause using Cox regression analyses, stratified according to geographic region, age, and sex. Population-attributable fractions were estimated for the 10-year incidence of cardiovascular disease and 10-year all-cause mortality. RESULTS: Among 1,518,028 participants (54.1% of whom were women) with a median age of 54.4 years, regional variations in the prevalence of the five modifiable risk factors were noted. Incident cardiovascular disease occurred in 80,596 participants during a median follow-up of 7.3 years (maximum, 47.3), and 177,369 participants died during a median follow-up of 8.7 years (maximum, 47.6). For all five risk factors combined, the aggregate global population-attributable fraction of the 10-year incidence of cardiovascular disease was 57.2% (95% confidence interval [CI], 52.4 to 62.1) among women and 52.6% (95% CI, 49.0 to 56.1) among men, and the corresponding values for 10-year all-cause mortality were 22.2% (95% CI, 16.8 to 27.5) and 19.1% (95% CI, 14.6 to 23.6). CONCLUSIONS: Harmonized individual-level data from a global cohort showed that 57.2% and 52.6% of cases of incident cardiovascular disease among women and men, respectively, and 22.2% and 19.1% of deaths from any cause among women and men, respectively, may be attributable to five modifiable risk factors. (Funded by the German Center for Cardiovascular Research (DZHK); ClinicalTrials.gov number, NCT05466825.).

Genome-wide meta-analysis identifies novel loci conferring risk of acne vulgaris.

Acne vulgaris is a common chronic skin disorder presenting with comedones, cystic structures forming within the distal hair follicle, and in most cases additionally with inflammatory skin lesions on the face and upper torso. We performed a genome-wide association study and meta-analysis of data from 34,422 individuals with acne and 364,991 controls from three independent European-ancestry cohorts. We replicated 19 previously implicated genome-wide significant risk loci and identified four novel loci [11q12.2 (FADS2), 12q21.1 (LGR5), 17q25.3 (FASN), and 22q12.1 (ZNRF3-KREMEN1)], bringing the total number of reported acne risk loci to 50. Our meta-analysis results explain 9.4% of the phenotypic variance of acne. A polygenic model of acne risk variants showed that individuals in the top 5% of the risk percentiles had a 1.62-fold (95% CI 1.47-1.78) increased acne risk relative to individuals with average risk (20-80% on the polygenic risk score distribution). Our findings highlight the Wnt and MAPK pathways as key factors in the genetic predisposition to acne vulgaris, together with the effects of genetic variation on the structure and maintenance of the hair follicle and pilosebaceous unit. Two novel loci, 11q12.2 and 17q25.3, contain genes encoding key enzymes involved in lipid biosynthesis pathways.

Genetic and modifiable risk factors combine multiplicatively in common disease.

BACKGROUND: The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized. OBJECTIVES: We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors. METHODS: We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions. RESULTS: In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer. CONCLUSIONS: Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed.

Precise, Genotype-First Breast Cancer Prevention: Experience With Transferring Monogenic Findings From a Population Biobank to the Clinical Setting.

Although hereditary breast cancer screening and management are well accepted and established in clinical settings, these efforts result in the detection of only a fraction of genetic predisposition at the population level. Here, we describe our experience from a national pilot study (2018-2021) in which 180 female participants of Estonian biobank (of >150,000 participants in total) were re-contacted to discuss personalized clinical prevention measures based on their genetic predisposition defined by 11 breast cancer-related genes. Our results show that genetic risk variants are relatively common in the average-risk Estonian population. Seventy-five percent of breast cancer cases in at-risk subjects occurred before the age of 50 years. Only one-third of subjects would have been eligible for clinical screening according to the current criteria. The participants perceived the receipt of genetic risk information as valuable. Fluent cooperation of project teams supported by state-of-art data management, quality control, and secure transfer can enable the integration of research results to everyday medical practice in a highly efficient, timely, and well-accepted manner. The positive experience in this genotype-first breast cancer study confirms the value of using existing basic genomic data from population biobanks for precise prevention.

Spectrum and frequency of CHEK2 variants in breast cancer affected and general population in the Baltic states region, initial results and literature review.

BACKGROUND: While BRCA1/2 gene mutational spectrum and clinical features are widely studied, there is limited data on breast cancer-predisposing non-BRCA pathogenic/likely pathogenic variants (PV/LPVs) in the Baltic states region. According to previous studies, CHEK2 is the most frequent moderate-risk breast cancer predisposition gene. The study aimed to analyse the frequency and mutational spectrum of CHEK2 PV/LPVs in the Baltic states region and perform a literature review on the subject. METHODS: The study includes two cohorts - population-based Estonian biobank (EstBB) (N-152 349) and breast cancer affected cases from Latvia (N-105). In the cohort from Latvia, CHEK2, BRCA1, BRCA2, PALB2 testing with next-generation sequencing (NGS) was carried out in selected breast cancer cases. In the EstBB, the full SNP genotyped dataset Global Screening Array (GSA) (N-152 349) was used to screen CHEK2 PV/LPVs and variants c.319+2T > A (p.(?)), c.444+1G>A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*) in CHEK2 are reported from this dataset. In addition, a subset of the EstBB (N-4776) underwent whole-genome sequencing (WGS, N-2420) and whole-exome sequencing (WES, N-2356) and founder variants c.470T > C (p.Ile157Thr), c.444+1G>A (p.(?)), c.1100delC (p.Thr367Metfs*15) in CHEK2 were reported from this dataset. Moreover, a literature overview was performed on April 1, 2021, using the PubMed search of keywords 'CHEK2', 'breast cancer', 'Estonia', 'Lithuania', 'Latvia', 'Poland', 'Belarus' and 'Russia'. RESULTS: In the breast cancer affected cohort from Latvia 6 CHEK2 variants, classified as PV/LPVs, were observed (6/105; 5.7%), including recurrent ones c.470T > C (p.Ile157Thr) (1.9%) and del5395(ex9-10del; (p.Met304Leufs*16)) (1.9%), as well as single ones - c.1100delC (p.Thr367Metfs*15) (1%) and c.444+1G>A (p.(?)) (1%). From EstBB NGS data (N-4776) CHEK2 variant c.470T > C (p.Ile157Thr) was detected in 8.6% of cases, c.1100delC (p.Thr367Metfs*15) in 0.6% and c.444+1G>A (p.(?)) in 0.2% of cases. In the EstBB full cohort of SNP array data (N-152 349) CHEK2 variant c.444+1G>A (p.(?)) was detected in 0.02% of cases, c.319+2T > A (p.(?)) in 0.09% of cases, c.433C > T (p.Arg145Trp) in 0.02% of cases and c.283C > T (p.Arg95*) in <0.001% of cases. For the literature review altogether, 49 PubMed articles were found, 23 of which were relevant, representing CHEK2 PV/LPVs in the population of interest. Ten publications are from Poland, eight from Russia, three from Latvia and two from Belarus. CONCLUSIONS: This study is the first combined report on complete CHEK2 PV/LPVs screening in selected breast cancer affected cases in Latvia and large-scale population screening in Estonia, providing insight into the CHEK2 mutational spectrum in the Baltic states region. The initial results are in line with other studies that CHEK2 PV/LPVs frequency is around 5-6% of selected breast cancer cases. Here we report three CHEK2 PV/LPV - c.319+2T > A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*), that are novel for the Baltic states region. This is also the first report on c.1100delC (p.Thr367Metfs*15) and c.444+1G>A (p.(?)) from the Baltic states. High population frequency of c.470T > C (p. Ile157Thr) (8.6%) continues to question the variant's pathogenicity in particular populations. Other findings are concordant with previous reports from Latvia and neighbouring populations.

The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium.

BACKGROUND: Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). METHODS AND FINDINGS: We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. CONCLUSIONS: This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer.

Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants.

Genotype-first approach allows to systematically identify carriers of pathogenic variants in BRCA1/2 genes conferring a high risk of familial breast and ovarian cancer. Participants of the Estonian biobank have expressed support for the disclosure of clinically significant findings. With an Estonian biobank cohort, we applied a genotype-first approach, contacted carriers, and offered return of results with genetic counseling. We evaluated participants' responses to and the clinical utility of the reporting of actionable genetic findings. Twenty-two of 40 contacted carriers of 17 pathogenic BRCA1/2 variants responded and chose to receive results. Eight of these 22 participants qualified for high-risk assessment based on National Comprehensive Cancer Network criteria. Twenty of 21 counseled participants appreciated being contacted. Relatives of 10 participants underwent cascade screening. Five of 16 eligible female BRCA1/2 variant carriers chose to undergo risk-reducing surgery, and 10 adhered to surveillance recommendations over the 30-month follow-up period. We recommend the return of results to population-based biobank participants; this approach could be viewed as a model for population-wide genetic testing. The genotype-first approach permits the identification of individuals at high risk who would not be identified by application of an approach based on personal and family histories only.

Propelling Health Care into the Twenties.

The scope and potential of personalised health care are underappreciated and underrealised, often because of resistance to change. The consequence is that many inadequacies of health care in Europe persist unnecessarily, and many opportunities for improvement are neglected. This article identifies the principal challenges, outlines possible approaches to resolving them, and highlights the benefits that could result from greater adoption of personalised health care. It locates the discussion in the context of European policy, focusing particularly on the most recent and authoritative reviews of health care in the EU Member States, and on the newly acquired spirit of readiness and pragmatism among European officials to embrace change and innovative technologies in a new decade. It highlights the attention now being given by policymakers to incentives, innovation, and investment as levers to improve European citizens' prospects in a rapidly evolving world, and how these distinct and disruptive themes contribute to a renaissance in thinking about delivering optimal health care in Europe. It explores the chances offered to patients by specific initiatives in health domains such as cancer and antimicrobial resistance, and by innovative science, novel therapies, earlier diagnosis tools, and deeper understanding of health promotion and prevention. And it reflects on how health care providers could benefit from a shift towards better primary care and towards deploying health data more effectively, including the use of artificial intelligence, coupled with a move to a smoother organisational/regulatory structure and realigned professional responsibilities. The conclusion is that preparing Europe's health care systems for the inevitable strains of the coming years is both possible and necessary. A more courageous approach to embracing personalised health care could guarantee the sustainability of Europe's health care systems before rising demands and exponential costs overwhelm them - an exercise in future-proofing, in ensuring that they are equipped to withstand whatever lies ahead. A focus on the potential and implementation of personalised care would permit more efficient use of resources and deliver better quality health-preserving care.

Publisher Correction: Personalized early detection and prevention of breast cancer: ENVISION consensus statement.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Personalized early detection and prevention of breast cancer: ENVISION consensus statement.

The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.

Identification of ALK in Thinness.

There is considerable inter-individual variability in susceptibility to weight gain despite an equally obesogenic environment in large parts of the world. Whereas many studies have focused on identifying the genetic susceptibility to obesity, we performed a GWAS on metabolically healthy thin individuals (lowest 6th percentile of the population-wide BMI spectrum) in a uniquely phenotyped Estonian cohort. We discovered anaplastic lymphoma kinase (ALK) as a candidate thinness gene. In Drosophila, RNAi mediated knockdown of Alk led to decreased triglyceride levels. In mice, genetic deletion of Alk resulted in thin animals with marked resistance to diet- and leptin-mutation-induced obesity. Mechanistically, we found that ALK expression in hypothalamic neurons controls energy expenditure via sympathetic control of adipose tissue lipolysis. Our genetic and mechanistic experiments identify ALK as a thinness gene, which is involved in the resistance to weight gain.

Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification.

BACKGROUND: Published genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aimed to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies. METHODS: Four different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) were compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors were studied in both cohorts. RESULTS: The metaGRS that combines two genetic risk scores (metaGRS2 - based on 75 and 898 Single Nucleotide Polymorphisms, respectively) had the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS2 corresponded to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10- 135) in the UK Biobank and accounting for family history marginally attenuated the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 7.8*10- 129). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS2 compared to women in the lowest 50% was 4.2 (95% CI 2.8 to 6.2, p = 8.1*10- 13). The different GRSs were only moderately correlated with each other and were associated with different known predictors of BC. The classification of genetic risk for the same individual varied considerably depending on the chosen GRS. CONCLUSIONS: We have shown that metaGRS2, that combined on the effects of more than 900 SNPs, provided best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS2 indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.

Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics.

Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance-based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall-Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

Noncoding RET variants explain the strong association with Hirschsprung disease in patients without rare coding sequence variant.

The pathogenesis of Hirschsprung disease is complex. Although the RET proto-oncogene is the most frequently affected gene in Hirschsprung disease, rare coding sequence variants explain only a small part of Hirschsprung disease cases. We aimed to assess the genetic background of Hirschsprung disease using a genome-wide association analysis combined with sequencing all RET exons in samples from 105 Hirschsprung disease cases (30 familial and 75 sporadic) and 386 controls. As expected, variants in or near RET showed the strongest overall association with Hirschsprung disease and the most statistically significant association was observed when using a recessive genetic model (rs2435357, NC_000010.10:g.43582056T > C; genotype TT, OR = 17.31, P = 1.462 × 10-21). Previously published associations in variants in SEMA (rs11766001, NC_000007.13:g.84145202A > C; allele C, OR = 2.268, P = 0.009533) and NRG1 (rs4541858, NC_000008.10:g.32410309A > G; allele G, OR = 1.567, P = 0.015; rs7835688, NC_000008.10:g.32411499G > C; allele C, OR = 1.567, P = 0.015) were also replicated in the genome-wide association analysis. Sequencing revealed a total of 12 exonic RET rare variants. Of these, eight amino acid changing rare variants and two frameshift variants caused or possibly caused Hirschsprung disease. Only a minority of the Hirschsprung disease cases (9/30 familial; 7/75 sporadic) carried one of the rare variants. Excluding the rare variant carriers from the genome-wide association analysis did not appreciably change the association of rs2435357 with Hirschsprung disease. We estimate that approximately two thirds of the sporadic cases may be statistically attributed to the recessive action of the common non-coding RET variants. Thus, even though most cases do not carry rare RET variants, combinations of rare variants and the common non-coding RET variant cause the majority of the cases in our population.

Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia.

PURPOSE: Large-scale, population-based biobanks integrating health records and genomic profiles may provide a platform to identify individuals with disease-predisposing genetic variants. Here, we recall probands carrying familial hypercholesterolemia (FH)-associated variants, perform cascade screening of family members, and describe health outcomes affected by such a strategy. METHODS: The Estonian Biobank of Estonian Genome Center, University of Tartu, comprises 52,274 individuals. Among 4776 participants with exome or genome sequences, we identified 27 individuals who carried FH-associated variants in the LDLR, APOB, or PCSK9 genes. Cascade screening of 64 family members identified an additional 20 carriers of FH-associated variants. RESULTS: Via genetic counseling and clinical management of carriers, we were able to reclassify 51% of the study participants from having previously established nonspecific hypercholesterolemia to having FH and identify 32% who were completely unaware of harboring a high-risk disease-associated genetic variant. Imaging-based risk stratification targeted 86% of the variant carriers for statin treatment recommendations. CONCLUSION: Genotype-guided recall of probands and subsequent cascade screening for familial hypercholesterolemia is feasible within a population-based biobank and may facilitate more appropriate clinical management.

Genome-wide association study and meta-analysis in Northern European populations replicate multiple colorectal cancer risk loci.

Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10-4 ; OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10-9 ; OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate < 0.1), but new risk loci were not found. These results replicate the effects of multiple loci on the risk of CRC and identify shared risk alleles between the Finnish population isolate and outbred populations.

Identifying pathways modulating sleep duration: from genomics to transcriptomics.

Recognizing that insights into the modulation of sleep duration can emerge by exploring the functional relationships among genes, we used this strategy to explore the genome-wide association results for this trait. We detected two major signalling pathways (ion channels and the ERBB signalling family of tyrosine kinases) that could be replicated across independent GWA studies meta-analyses. To investigate the significance of these pathways for sleep modulation, we performed transcriptome analyses of short sleeping flies' heads (knockdown for the ABCC9 gene homolog; dSur). We found significant alterations in gene-expression in the short sleeping knockdowns versus controls flies, which correspond to pathways associated with sleep duration in our human studies. Most notably, the expression of Rho and EGFR (members of the ERBB signalling pathway) genes was down- and up-regulated, respectively, consistently with the established role of these genes for sleep consolidation in Drosophila. Using a disease multifactorial interaction network, we showed that many of the genes of the pathways indicated to be relevant for sleep duration had functional evidence of their involvement with sleep regulation, circadian rhythms, insulin secretion, gluconeogenesis and lipogenesis.

Genotype-covariate interaction effects and the heritability of adult body mass index.

Obesity is a worldwide epidemic, with major health and economic costs. Here we estimate heritability for body mass index (BMI) in 172,000 sibling pairs and 150,832 unrelated individuals and explore the contribution of genotype-covariate interaction effects at common SNP loci. We find evidence for genotype-age interaction (likelihood ratio test (LRT) = 73.58, degrees of freedom (df) = 1, P = 4.83 × 10-18), which contributed 8.1% (1.4% s.e.) to BMI variation. Across eight self-reported lifestyle factors, including diet and exercise, we find genotype-environment interaction only for smoking behavior (LRT = 19.70, P = 5.03 × 10-5 and LRT = 30.80, P = 1.42 × 10-8), which contributed 4.0% (0.8% s.e.) to BMI variation. Bayesian association analysis suggests that BMI is highly polygenic, with 75% of the SNP heritability attributable to loci that each explain <0.01% of the phenotypic variance. Our findings imply that substantially larger sample sizes across ages and lifestyles are required to understand the full genetic architecture of BMI.