The mouse gene retinal degeneration (rd) may reduce the number of neurons present in the adult hippocampal dentate gyrus

C57BL/6J and C57BL/6J-rd le Gus-s^h mice, congenics at therd locus, were compared with respect to number of granule cells and presumed pyramidal basket cells in the hippocampal dentate gyrus. Number of both types of neurons were less inrd/rd mice than in ±/± mice. Therd gene may be responsible.     

Contribution of metabolic risk factors and lifestyle behaviors to cardiovascular disease: A mendelian randomization study

Background and aimsEtiologic associations between some modifiable factors (metabolic risk factors and lifestyle behaviors) and cardiovascular disease (CVD) remain unclear. To identify targets for CVD prevention, we evaluated the causal associations of these factors with coronary artery disease (CAD) and ischemic stroke using a two-sample Mendelian randomization (MR) method.Methods and resultsPreviously published genome-wide association studies (GWASs) for blood pressure (BP), glucose, lipids, overweight, smoking, alcohol intake, sedentariness, and education were used to identify instruments for 15 modifiable factors. We extracted effects of the genetic variants used as instruments for the exposures on coronary artery disease (CAD) and ischemic stroke from large GWASs (N = 60 801 cases/123 504 controls for CAD and N = 40 585 cases/406 111 controls for ischemic stroke). Genetically predicted hypertension (CAD: OR, 5.19 [95% CI, 4.21–6.41]; ischemic stroke: OR, 4.92 [4.12–5.86]), systolic BP (CAD: OR, 1.03 [1.03–1.04]; ischemic stroke: OR, 1.03 [1.03–1.03]), diastolic BP (CAD: OR, 1.05 [1.05–1.06]; ischemic stroke: OR, 1.05 [1.04–1.05]), type 2 diabetes (CAD: OR, 1.11 [1.08–1.15]; ischemic stroke: OR, 1.07 [1.04-1.10]), smoking initiation (CAD: OR, 1.26 [1.18–1.35]; ischemic stroke: OR, 1.24 [1.16–1.33]), educational attainment (CAD: OR, 0.62 [0.58–0.66]; ischemic stroke: OR, 0.68 [0.63–0.72]), low-density lipoprotein cholesterol (CAD: OR, 1.55 [1.41–1.71]), high-density lipoprotein cholesterol (CAD: OR, 0.82 [0.74–0.91]), triglycerides (CAD: OR, 1.29 [1.14–1.45]), body mass index (CAD: OR, 1.25 [1.19–1.32]), and alcohol dependence (OR, 1.04 [1.03–1.06]) were causally related to CVD.ConclusionThis systematic MR study identified 11 modifiable factors as causal risk factors for CVD, indicating that these factors are important targets for preventing CVD.     

A genetic link between type 2 diabetes and prostate cancer

Epidemiological studies suggest that men with type 2 diabetes are less likely than non-diabetic men to develop prostate cancer. The cause of this association is not known. Recent genetic studies have highlighted a potential genetic link between the two diseases. Two studies have identified a version (allele) of a variant in the HNF1B (also known as TCF2) gene that predisposes to type 2 diabetes, and one of them showed that the same allele protects men from prostate cancer. Other, separate, studies have identified different variants in the JAZF1 gene, one associated with type 2 diabetes, another associated with prostate cancer. These findings are unlikely to completely explain the epidemiological association between the two diseases but they provide new insight into a possible direct causal link, rather than one that is confounded or biased in some way.     

Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome‐wide associations

Genome‐wide association studies (GWAS) using high‐density genotyping platforms offer an unbiased strategy to identify new candidate genes for osteoporosis. It is imperative to be able to clearly distinguish signal from noise by focusing on the best phenotype in a genetic study. We performed GWAS of multiple phenotypes associated with fractures [bone mineral density (BMD), bone quantitative ultrasound (QUS), bone geometry, and muscle mass] with approximately 433,000 single‐nucleotide polymorphisms (SNPs) and created a database of resulting associations. We performed analysis of GWAS data from 23 phenotypes by a novel modification of a block clustering algorithm followed by gene‐set enrichment analysis. A data matrix of standardized regression coefficients was partitioned along both axes—SNPs and phenotypes. Each partition represents a distinct cluster of SNPs that have similar effects over a particular set of phenotypes. Application of this method to our data shows several SNP‐phenotype connections. We found a strong cluster of association coefficients of high magnitude for 10 traits (BMD at several skeletal sites, ultrasound measures, cross‐sectional bone area, and section modulus of femoral neck and shaft). These clustered traits were highly genetically correlated. Gene‐set enrichment analyses indicated the augmentation of genes that cluster with the 10 osteoporosis‐related traits in pathways such as aldosterone signaling in epithelial cells, role of osteoblasts, osteoclasts, and chondrocytes in rheumatoid arthritis, and Parkinson signaling. In addition to several known candidate genes, we also identified PRKCH and SCNN1B as potential candidate genes for multiple bone traits. In conclusion, our mining of GWAS results revealed the similarity of association results between bone strength phenotypes that may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in identifying novel genes and pathways that underlie several correlated phenotypes, as well as in deciphering genetic and phenotypic modularity underlying osteoporosis risk. © 2011 American Society for Bone and Mineral Research.     

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.     

孟德尔随机化中多效性偏倚校正方法简介

孟德尔随机化以遗传变异作为工具变量，对感兴趣的暴露因素与结局的因果关联进行估计及评价。遗传变异作为有效工具变量需要满足强关联假设及无多效性假设。然而，由于遗传变异与表型性状间存在复杂的生物学效应，其作为工具变量的多效性往往无法避免。基于此，本文分别从工具变量筛选、无效工具变量检验、校正多效性的模型构建以及敏感性分析等方面介绍无效工具变量的多效性偏倚校正方法。在实际应用中，研究者应结合数据类型、样本含量、分析假设等多个方面选择合适的方法进行分析与推断，从而得到一致、稳健的因果效应估计量。     

HLA-disease association and pleiotropy landscape in over 235,000 Finns

The human leukocyte antigen (HLA) system is the single most important genetic susceptibility factor for many autoimmune diseases and immunological traits. For systematic population-level analysis of HLA-phenotype association landscape we imputed the alleles of classical HLA genes in a discovery cohort of 146,630 and replication cohort of 89,340 Finns of whom SNP genotype data and 3,355 disease phenotypes were available as part of the FinnGen project. In total, 3,649 statistically significant single HLA allele associations in 368 phenotypes were found. Known susceptibility associations clearly dominated the landscape but we discovered also a few previously poorly established HLA associations such as DQA1*01:03 and DQB1*06:03 with mental and behavioural disorders due to cannabinoids (p-value = 10^-5; beta = 0.6). As certain HLAs were found to be involved in both autoimmune and infectious diseases, we studied further the independence of their associations and statistical pleiotropy. We found that altogether 11 shared HLA alleles were associated independently with both autoimmune and infectious diseases. The most prominent of these were DQA1*03:01 and DQB1*03:02 both of which associated with three infectious and three autoimmune phenotypes. All the shared HLAs showed risk effects in both disease groups, suggesting that infections can increase the risk for autoimmune diseases. The population-level landscape analysis is an excellent resource for estimating the contribution and genetic models of HLA genes in many different phenotypes and for fine-mapping primary associations.     

No association between alcohol consumption and risk of atrial fibrillation: A two-sample Mendelian randomization study

Background and aimsAlthough many observational studies have suggested that alcohol intake was associated with incident atrial fibrillation (AF), controversy remains. This study aimed to examine the causal association of alcohol intake with the risk of AF.Methods and resultsTwo-sample Mendelian randomization (MR) analysis was performed to estimate the causal effects of alcohol consumption, alcohol dependence, or alcohol use disorder identification test (AUDIT) scores on AF. Summary data on single nucleotide polymorphisms (SNPs) associated with AF were obtained from a genome-wide association study (GWAS) with up to 1,030,836 participants. The fixed- and random-effect inverse-variance weighted (IVW) methods were used to calculate the overall causal effects. MR analysis revealed nonsignificant association of genetically predicted alcohol consumption with risk of AF using fixed- and random-effect IVW approaches (odds ratio (OR) [95% confidence interval (CI)] = 1.004 [0.796–1.266], P = 0.975; OR [95% CI] = 1.004 [0.766–1.315], P = 0.979). Genetically predicted alcohol dependence was also not causally associated with AF in the fixed- and random-effect IVW analyses (OR [95% CI] = 1.012 [0.978–1.048], P = 0.490; OR [95% CI] = 1.012 [0.991–1.034], P = 0.260). There was no significantly causal association between AUDIT and AF in the fixed- and random-effect IVW analyses (OR [95% CI] = 0.889 [0.433–1.822], P = 0.748; OR [95% CI] = 0.889 [0.309–2.555], P = 0.827). Sensitivity analyses indicated no evidence of pleiotropy and heterogeneity in statistical models.ConclusionsThis MR study did not find evidence of a causal association between alcohol intake and AF.     

Female fertility and longevity

Does bearing children shorten a woman’s life expectancy? Pleiotropic theories of aging predict that it should, and in particular, the Disposable Soma theory predicts unequivocally that this effect should be inescapable. But many demographic studies, historic and current, have found no such effect. In this context, the Caerphilly cohort study stands apart as the sole test that corroborates the theory. Why has this study found an effect that others fail to see? Their analysis is based on Poisson regression, a statistical technique that is accurate only if the underlying data are Poisson-distributed. But the distribution of the number of children born to women in the Caerphilly database departs strongly from Poisson at the high end. This makes the result overly sensitive to a handful of women with 15 children or more who lived before 1700. When these five women are removed from a database of more than 2,900, the Poisson regression no longer shows a significant result. Bilinear regression relating life span to fertility and date of birth results in a small positive coefficient for fertility, in agreement with the main trend of reported results.