Confounding from Cryptic Relatedness in Case-Control Association Studies

Case-control association studies are widely used in the search for genetic variants that contribute to human diseases. It has long been known that such studies may suffer from high rates of false positives if there is unrecognized population structure. It is perhaps less widely appreciated that so-called “cryptic relatedness” (i.e., kinship among the cases or controls that is not known to the investigator) might also potentially inflate the false positive rate. Until now there has been little work to assess how serious this problem is likely to be in practice. In this paper, we develop a formal model of cryptic relatedness, and study its impact on association studies. We provide simple expressions that predict the extent of confounding due to cryptic relatedness. Surprisingly, these expressions are functions of directly observable parameters. Our analytical results show that, for well-designed studies in outbred populations, the degree of confounding due to cryptic relatedness will usually be negligible. However, in contrast, studies where there is a sampling bias toward collecting relatives may indeed suffer from excessive rates of false positives. Furthermore, cryptic relatedness may be a serious concern in founder populations that have grown rapidly and recently from a small size. As an example, we analyze the impact of excess relatedness among cases for six phenotypes measured in the Hutterite population

Egalitarian justice and expected value

According to all-luck egalitarianism, the differential distributive effects of both brute luck, which defines the outcome of risks which are not deliberately taken, and option luck, which defines the outcome of deliberate gambles, are unjust. Exactly how to correct the effects of option luck is, however, a complex issue. This article argues that (a) option luck should be neutralized not just by correcting luck among gamblers, but among the community as a whole, because it would be unfair for gamblers as a group to be disadvantaged relative to non-gamblers by bad option luck; (b) individuals should receive the warranted expected results of their gambles, except insofar as individuals blamelessly lacked the ability to ascertain which expectations were warranted; and (c) where societal resources are insufficient to deliver expected results to gamblers, gamblers should receive a lesser distributive share which is in proportion to the expected results. Where all-luck egalitarianism is understood in this way, it allows risk-takers to impose externalities on non-risk-takers, which seems counterintuitive. This may, however, be an advantage as it provides a luck egalitarian rationale for assisting ‘negligent victims’

A Map of Recent Positive Selection in the Human Genome

The identification of signals of very recent positive selection provides information about the adaptation of modern humans to local conditions. We report here on a genome-wide scan for signals of very recent positive selection in favor of variants that have not yet reached fixation. We describe a new analytical method for scanning single nucleotide polymorphism (SNP) data for signals of recent selection, and apply this to data from the International HapMap Project. In all three continental groups we find widespread signals of recent positive selection. Most signals are region-specific, though a significant excess are shared across groups. Contrary to some earlier low resolution studies that suggested a paucity of recent selection in sub-Saharan Africans, we find that by some measures our strongest signals of selection are from the Yoruba population. Finally, since these signals indicate the existence of genetic variants that have substantially different fitnesses, they must indicate loci that are the source of significant phenotypic variation. Though the relevant phenotypes are generally not known, such loci should be of particular interest in mapping studies of complex traits. For this purpose we have developed a set of SNPs that can be used to tag the strongest ∼250 signals of recent selection in each population

Genome skimming elucidates the evolutionary history of Octopoda

Phylogenies for Octopoda have, until now, been based on morphological characters or a few genes. Here we provide the complete mitogenomes and the nuclear 18S and 28S ribosomal genes of twenty Octopoda specimens, comprising 18 species of Cirrata and Incirrata, representing 13 genera and all five putative families of Cirrata (Cirroctopodidae, Cirroteuthidae, Grimpoteuthidae, Opisthoteuthidae and Stauroteuthidae) and six families of Incirrata (Amphitretidae, Argonautidae, Bathypolypodidae, Eledonidae, Enteroctopodidae, and Megaleledonidae) which were assembled using genome skimming. Phylogenetic trees were built using Maximum Likelihood and Bayesian Inference with several alignment matrices. All mitochondrial genomes had the ‘typical’ genome composition and gene order previously reported for octopodiforms, except Bathypolypus ergasticus, which appears to lack ND5, two tRNA genes that flank ND5 and two other tRNA genes. Argonautoidea was revealed as sister to Octopodidae by the mitochondrial protein-coding gene dataset, however, it was recovered as sister to all other incirrate octopods with strong support in an analysis using nuclear rRNA genes. Within Cirrata, our study supports two existing classifications suggesting neither is likely in conflict with the true evolutionary history of the suborder. Genome skimming is useful in the analysis of phylogenetic relationships within Octopoda; inclusion of both mitochondrial and nuclear data may be key

Tri-critical behavior in rupture induced by disorder

We discover a qualitatively new behavior for systems where the load transfer has limiting stress amplification as in real fiber composites. We find that the disorder is a relevant field leading to tri--criticality, separating a first-order regime where rupture occurs without significant precursors from a second-order regime where the macroscopic elastic coefficient exhibit power law behavior. Our results are based on analytical analysis of fiber bundle models and numerical simulations of a two-dimensional tensorial spring-block system in which stick-slip motion and fracture compete.Comment: Revtex, 10 pages, 4 figures available upon reques

The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits

PMCID: PMC3410907This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Pressure Dependence of the Elastic Moduli in Aluminum Rich Al-Li Compounds

I have carried out numerical first principles calculations of the pressure dependence of the elastic moduli for several ordered structures in the Aluminum-Lithium system, specifically FCC Al, FCC and BCC Li, L1_2 Al_3Li, and an ordered FCC Al_7Li supercell. The calculations were performed using the full potential linear augmented plane wave method (LAPW) to calculate the total energy as a function of strain, after which the data was fit to a polynomial function of the strain to determine the modulus. A procedure for estimating the errors in this process is also given. The predicted equilibrium lattice parameters are slightly smaller than found experimentally, consistent with other LDA calculations. The computed elastic moduli are within approximately 10% of the experimentally measured moduli, provided the calculations are carried out at the experimental lattice constant. The LDA equilibrium shear modulus C11-C12 increases from 59.3 GPa in Al, to 76.0 GPa in Al_7Li, to 106.2 GPa in Al_3Li. The modulus C_44 increases from 38.4 GPa in Al to 46.1 GPa in Al_7Li, then falls to 40.7 GPa in Al_3Li. All of the calculated elastic moduli increase with pressure with the exception of BCC Li, which becomes elastically unstable at about 2 GPa, where C_11-C_12 vanishes.Comment: 17 pages (REVTEX) + 7 postscript figure

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis