Supplementary_figure_and_Tables - Transcriptome-Wide Association Study Identifies Susceptibility Loci and Genes for Age at Natural Menopause

<p>Supplementary_figure_and_Tables for Transcriptome-Wide Association Study Identifies Susceptibility Loci and Genes for Age at Natural Menopause by Jiajun Shi, Lang Wu, Bingshan Li, Yingchang Lu, Xingyi Guo, Qiuyin Cai, Jirong Long, Wanqing Wen, Wei Zheng, and Xiao-Ou Shu in Reproductive Sciences</p

Association between baseline δ-5 and δ-6 desaturase activity and incident coronary heart disease (CHD).

1<p>δ-5 and δ-6 desaturase activities were assessed by the ratio of C20∶4n-6 to C20∶3n-6 and the ratio of C18∶3n-6 to C18∶2n-6 in plasma cholesteryl esters, respectively and median ratios in each quintile are listed between brackets.</p>2<p>From models with desaturase activity included as a continuous variable.</p>3<p>Model 1 was adjusted for age and sex.</p>4<p>Model 2 was adjusted for age, sex, systolic blood pressure, hypertensive medication use, current smoking, and diabetes.</p>5<p>Model 3 was adjusted for all covariates in model 2, total cholesterol, and high-density lipoprotein cholesterol.</p>6<p>Model 4 was adjusted for all covariates in model 3 and percentages of C22∶6n-3 (DHA) in plasma cholesteryl esters.</p

Baseline characteristics of sub-cohort subjects and cases of incident coronary heart disease in the CAREMA cohort study¹.

1<p>Data are expressed as mean ± SD or n (%) unless otherwise indicated. HDL: high-density lipoprotein; MI: myocardial infarction; and HR (95% CI): hazard ratio and 95% confidence interval.</p>2<p>Including 84 cases.</p>3<p>Hazard ratios were calculated per unit increase in total cholesterol, HDL cholesterol, and systolic blood pressure, and for the presence of the categorical traits.</p>4<p>All variables were added into one multivariable Cox proportional hazards model.</p

Association of rs174547 in <i>FADS1</i> with baseline PUFAs in plasma cholesteryl esters and desaturase activities in the sub-cohort (n = 1246)¹.

1<p>77 subjects in the subcohort had missing values for rs174547. PUFAs: polyunsaturated fatty acids.</p>2<p>General linear models were used, and all values are mean ± SEM, adjusted for age and sex.</p>3<p>Only few subjects were successfully measured (AA = 161, AG = 185, and GG = 42).</p>4<p>δ-5 and δ-6 desaturase activities were assessed by the ratio of C20∶4n-6 to C20∶3n-6 and C18∶3n-6 to C18∶2n-6 in plasma cholesteryl esters, respectively.</p

Effect of genotypes of rs174547 on synthesis of PUFAs in the n-3 and n-6 pathways.

<p>Measurements of n-3 and n-6 polyunsaturated fatty acid (PUFA) levels in plasma cholesteryl esters in the sub-cohort of CAREMA study (n = 1246, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041681#pone-0041681-t002" target="_blank">Table 2</a>). The three bars in each of the smaller plots represent levels of fatty acids (%) in individuals who carry AA, AG and GG genotypes of rs174547, respectively.</p

Validation of the <i>KCNK3</i> rs2586886 associations with BP in independent multi-ethnic populations.

<p>Validation of the <i>KCNK3</i> rs2586886 associations with BP in independent multi-ethnic populations.</p

Descriptive characteristics^a of the PAGE and FBBP studies by race/ethnicity.

<p>Descriptive characteristics<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164132#t001fn002" target="_blank">^a</a> of the PAGE and FBBP studies by race/ethnicity.</p

Enrichment for functional annotations and cell-type groups using stratified LD score regression.

<p><b>A.</b> Enrichment estimates of 24 main annotations for each of four BP traits. Annotations are ordered by size. Error bars represent jackknife standard errors around the estimates of enrichment, and stars indicate significance at P < 0.05 after Bonferroni correction for 24 hypotheses tested and four BP traits. <b>B.</b> Significance of enrichment of 10 cell-type groups for four BP traits. Dotted line and stars indicate significance at P < 0.05 after Bonferroni correction for 10 hypotheses tested and four BP traits.</p

Intelligent Forecasting of Electricity Demand

In this paper, a number of approaches to the modelling of electricity demand, on a variety of time-scales, are considered. These approaches fall under the category of 'intelligent' systems engineering, where techniques such as neural networks, fuzzy logic and genetic algorithms are employed. The paper attempts to give some motivation for the employment of such techniques, while also making some effort to be realistic about the limitations of such methods, in particular a number of important caveats that should be borne in mind when utilising these techniques within the current application domain. In general, the electricity demand data is modelled as a time series, but one application considered involves application of linguistic modelling to capture operator expertise