Systems and organizations: Distal and proximal thinking

The paper introduces the contributions to this special issue ofSystems Practice on Systems and Organizations: New Directions in terms ofdistal andproximal thinking. Distal thinking refers to ready-made concepts, to the finished effects and outcomes of thought and action; proximal thinking, to process and event, to the continuous and unfinished. The papers presented here deal with various aspects of the distal/proximal distinction in social systems and organizations, and especially draw out the implications of recent work in information technology, sociology of technology, accounting theory, and organization studies for a proximal conception of systems and organizations.     

A study of standardization of variables in cluster analysis

A methodological problem in applied clustering involves the decision of whether or not to standardize the input variables prior to the computation of a Euclidean distance dissimilarity measure. Existing results have been mixed with some studies recommending standardization and others suggesting that it may not be desirable. The existence of numerous approaches to standardization complicates the decision process. The present simulation study examined the standardization problem. A variety of data structures were generated which varied the intercluster spacing and the scales for the variables. The data sets were examined in four different types of error environments. These involved error free data, error perturbed distances, inclusion of outliers, and the addition of random noise dimensions. Recovery of true cluster structure as found by four clustering methods was measured at the correct partition level and at reduced levels of coverage. Results for eight standardization strategies are presented. It was found that those approaches which standardize by division by the range of the variable gave consistently superior recovery of the underlying cluster structure. The result held over different error conditions, separation distances, clustering methods, and coverage levels. The traditionalz-score transformation was found to be less effective in several situations.     

Common variants near MC4R are associated with fat mass, weight and risk of obesity

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.     

Systematic assessment of copy number variant detection via genome-wide SNP genotyping

SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.     

A defective response to Hedgehog signaling in disorders of cholesterol biosynthesis

Smith-Lemli-Opitz syndrome (SLOS), desmosterolosis and lathosterolosis are human syndromes caused by defects in the final stages of cholesterol biosynthesis. Many of the developmental malformations in these syndromes occur in tissues and structures whose embryonic patterning depends on signaling by the Hedgehog (Hh) family of secreted proteins. Here we report that response to the Hh signal is compromised in mutant cells from mouse models of SLOS and lathosterolosis and in normal cells pharmacologically depleted of sterols. We show that decreasing levels of cellular sterols correlate with diminishing responsiveness to the Hh signal. This diminished response occurs at sterol levels sufficient for normal autoprocessing of Hh protein, which requires cholesterol as cofactor and covalent adduct. We further find that sterol depletion affects the activity of Smoothened (Smo), an essential component of the Hh signal transduction apparatus.