Genomic prediction of alcohol-related morbidity and mortality

While polygenic risk scores (PRS) have been shown to predict many diseases and risk factors, the potential of genomic prediction in harm caused by alcohol use has not yet been extensively studied. Here, we built a novel polygenic risk score of 1.1 million variants for alcohol consumption and studied its predictive capacity in 96,499 participants from the FinnGen study and 39,695 participants from prospective cohorts with detailed baseline data and up to 25 years of follow-up time. A 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption (CI = 9.85-12.58 g, p = 2.3 x 10(-58)). The PRS was associated with alcohol-related morbidity (4785 incident events) and the risk estimate between the highest and lowest quintiles of the PRS was 1.83 (95% CI = 1.66-2.01, p = 1.6 x 10(-36)). When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels in 28,639 participants with comprehensive baseline data from prospective cohorts, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI = 1.26-1.99, p = 8.2 x 10(-5)). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI = 1.20-1.47, p = 4.5 x 10(-8)) in the adjusted model. In conclusion, the PRS for alcohol consumption independently associates for both alcohol-related morbidity and all-cause mortality. Together, these findings underline the importance of heritable factors in alcohol-related health burden while highlighting how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes

Genetic and environmental influence on lung function impairment in Swedish twins

<p>Abstract</p> <p>Background</p> <p>The understanding of the influence of smoking and sex on lung function and symptoms is important for understanding diseases such as COPD. The influence of both genes and environment on lung function, smoking behaviour and the presence of respiratory symptoms has previously been demonstrated for each of these separately. Hence, smoking can influence lung function by co-varying not only as an environmental factor, but also by shared genetic pathways. Therefore, the objective was to evaluate heritability for different aspects of lung function, and to investigate how the estimates are affected by adjustments for smoking and respiratory symptoms.</p> <p>Methods</p> <p>The current study is based on a selected sample of adult twins from the Swedish Twin Registry. Pairs were selected based on background data on smoking and respiratory symptoms collected by telephone interview. Lung function was measured as FEV₁, VC and DLco. Pack years were quantified, and quantitative genetic analysis was performed on lung function data adjusting stepwise for sex, pack years and respiratory symptoms.</p> <p>Results</p> <p>Fully adjusted heritability for VC was 59% and did not differ by sex, with smoking and symptoms explaining only a small part of the total variance. Heritabilities for FEV₁and DLco were sex specific. Fully adjusted estimates were10 and 15% in men and 46% and 39% in women, respectively. Adjustment for smoking and respiratory symptoms altered the estimates differently in men and women. For FEV₁and DLco, the variance explained by smoking and symptoms was larger in men. Further, smoking and symptoms explained genetic variance in women, but was primarily associated with shared environmental effects in men.</p> <p>Conclusion</p> <p>Differences between men and women were found in how smoking and symptoms influence the variation in lung function. Pulmonary gas transfer variation related to the menstrual cycle has been shown before, and the findings regarding DLco in the present study indicates gender specific environmental susceptibility not shown before. As a consequence the results suggest that patients with lung diseases such as COPD could benefit from interventions that are sex specific.</p

Do intrauterine or genetic influences explain the foetal origins of chronic disease? A novel experimental method for disentangling effects

Background There is much evidence to suggest that risk for common clinical disorders begins in foetal life. Exposure to environmental risk factors however is often not random. Many commonly used indices of prenatal adversity (e.g. maternal gestational stress, gestational diabetes, smoking in pregnancy) are influenced by maternal genes and genetically influenced maternal behaviour. As mother provides the baby with both genes and prenatal environment, associations between prenatal risk factors and offspring disease maybe attributable to true prenatal risk effects or to the "confounding" effects of genetic liability that are shared by mother and offspring. Cross-fostering designs, including those that involve embryo transfer have proved useful in animal studies. However disentangling these effects in humans poses significant problems for traditional genetic epidemiological research designs. Methods We present a novel research strategy aimed at disentangling maternally provided pre-natal environmental and inherited genetic effects. Families of children aged 5 to 9 years born by assisted reproductive technologies, specifically homologous IVF, sperm donation, egg donation, embryo donation and gestational surrogacy were contacted through fertility clinics and mailed a package of questionnaires on health and mental health related risk factors and outcomes. Further data were obtained from antenatal records. Results To date 741 families from 18 fertility clinics have participated. The degree of association between maternally provided prenatal risk factor and child outcome in the group of families where the woman undergoing pregnancy and offspring are genetically related (homologous IVF, sperm donation) is compared to association in the group where offspring are genetically unrelated to the woman who undergoes the pregnancy (egg donation, embryo donation, surrogacy). These comparisons can be then examined to infer the extent to which prenatal effects are genetically and environmentally mediated. Conclusion A study based on children born by IVF treatment and who differ in genetic relatedness to the woman undergoing the pregnancy is feasible. The present report outlines a novel experimental method that permits disaggregation of maternally provided inherited genetic and post-implantation prenatal effects

Genetic effects influencing risk for major depressive disorder in China and Europe

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (similar to 30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor = 8.08) but failed to replicate in an independent European sample (P= 0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP <5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P <5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.Peer reviewe

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BACKGROUND Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation. CONCLUSION This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders. They are heritable and etiologically related behaviors that have been resistant to gene discovery efforts. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures