Self-Organising Map Approach to Individual Profiles: Age, Sex and Culture in Internet Dating

A marked feature of recent developments in the networked society has been the growth in the number of people making use of Internet dating services. These services involve the accumulation of large amounts of personal information which individuals utilise to find others and potentially arrange offline meetings. The consequent data represent a challenge to conventional analysis, for example, the service that provided the data used in this paper had approximately 5,000 users all of whom completed an extensive questionnaire resulting in some 300 parameters. This creates an opportunity to apply innovative analytical techniques that may provide new sociological insights into complex data. In this paper we utilise the self-organising map (SOM), an unsupervised neural network methodology, to explore Internet dating data. The resulting visual maps are used to demonstrate the ability of SOMs to reveal interrelated parameters. The SOM process led to the emergence of correlations that were obscured in the original data and pointed to the role of what we call \'cultural age\' in the profiles and partnership preferences of the individuals. Our results suggest that the SOM approach offers a well established methodology that can be easily applied to complex sociological data sets. The SOM outcomes are discussed in relation to other research about identifying others and forming relationships in a network society.Self-Organising Map; Neural Network; Complex Data; Internet Dating; Age; Sex; Culture; Relationship; Visualisation

Genetic support for a causal role of insulin resistance on circulating branched-chain amino acids and inflammation

Objective: Insulin resistance has deleterious effects on cardiometabolic disease. We used Mendelian randomization analyses to clarify the causal relationships of insulin resistance (IR) on circulating blood-based metabolites to shed light on potential mediators of the IR to cardiometabolic disease relationship.Research design and methods: We used 53 single nucleotide polymorphisms associated with IR from a recent genome-wide association study (GWAS) to explore their effects on circulating lipids and metabolites. We used published summary-level data from two GWASs of European individuals; data on the exposure (IR) were obtained from meta-GWASs of 188,577 individuals, and data on the outcomes (58 metabolic measures assessed by nuclear magnetic resonance) were taken from a GWAS of 24,925 individuals.Results: One-SD genetically elevated IR (equivalent to 55% higher geometric mean of fasting insulin, 0.89 mmol/L higher triglycerides, and 0.46 mmol/L lower HDL cholesterol) was associated with higher concentrations of all branched-chain amino acids (BCAAs)—isoleucine (0.56 SD; 95% CI 0.43, 0.70), leucine (0.42 SD; 95% CI 0.28, 0.55), and valine (0.26 SD; 95% CI 0.12, 0.39)—as well as with higher glycoprotein acetyls (an inflammation marker) (0.47 SD; 95% CI 0.32, 0.62) (P < 0.0003 for each). Results were broadly consistent when using multiple sensitivity analyses to account for potential genetic pleiotropy.Conclusions: We provide robust evidence that IR causally affects each individual BCAA and inflammation. Taken together with existing studies, this implies that BCAA metabolism lies on a causal pathway from adiposity and IR to type 2 diabetes