Association Testing of Previously Reported Variants in a Large Case-Control Meta-analysis of Diabetic Nephropathy

We formed the GEnetics of Nephropathy–an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10−9). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

New susceptibility loci associated with kidney disease in type 1 diabetes

WOS:000309817900008Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ∼2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2×10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0×10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1×10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.Peer reviewe

Conclusion: Perspectives on the Politics of Abortion

Perspectives on the Politics of Abortion examines the abortion issue from ethical, empirical, and legal angles and offers some rather unconventional analyses and surprising conclusions with regard to this familiar issue. One chapter argues that the emphasis on rights has made illegal and occasionally violent activity on the part of pro-life activists increasingly likely. Another chapter suggests that abortion is an instance of the more general right to self-defense. A chapter considers the problem of abortion from the standpoint of participants in the political process. And chapters examine the political tactics of the Roman Catholic Church and abortion rights in terms of constitutional due process. This important volume adds new voices and perspectives to the abortion debate

Association testing of previously reported genetic variants in a large case-control meta-analysis of diabetic nephropathy:Oral Presentation

Failure detectors — oracles that provide information about process crashes — are an important abstraction for crash tolerance in distributed systems. The generality of failure-detector theory, while providing great expressiveness, poses significant challenges in developing a robust hierarchy of failure detectors. We address some of these challenges by proposing (1) a variant of failure detectors called asynchronous failure detectors and (2) an associated modeling framework. Unlike the traditional failure-detector framework, our framework eschews real-time completely. We show that asynchronous failure detectors are sufficiently expressive to include several popular failure detectors including, but not limited to, the canonical Chandra-Toueg failure detectors, Σ and other quorum failure detectors, Ω, anti-Ω, Ωk, and Ψk. Additionally, asynchronous failure detectors satisfy many desirable properties: they are self-implementable, guarantee that stronger asynchronous failure-detectors solve harder problems, and ensure that their outputs encode no information other than the set of crashed processes. We introduce the notion of a failure detector being representative for a problem to capture the idea that some problems encode the same information about process crashes as their weakest failure detectors do. We show that a large class of problems, called bounded problems, do not have representative failure detectors. Finally, we use the asynchronous failure-detector framework to show how sufficiently strong AFDs circumvent the impossibility of consensus in asynchronous systems.