Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV1] and its ratio to forced vital capacity [FEV1/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV1 and FEV1/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08–1.43] for PTRS versus 1.10 [0.96–1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10−16 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk

Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry

Interconnecting Single-Phase Generation to the Utility Distribution System

One potentially large source of underutilized distributed generation (DG) capacity exists in single-phase standby backup gensets on farms served from single-phase feeder laterals. Utilizing the excess capacity would require interconnecting to the utility system. Connecting single-phase gensets to the utility system presents some interesting technical issues that have not been previously investigated. This paper addresses several of the interconnection issues associated with this form of DG including voltage regulation, harmonics, overcurrent protection, and islanding. A significant amount of single-phase DG can be accommodated by the utility distribution system, but there are definite limitations due to the nature and location of the DG. These limitations may be more restrictive than is commonly assumed for three-phase DG installed on stronger parts of the electric distribution system

Methodology for the analysis of voltage unbalance in networks with single phase distributed generation

A sequence networks-based methodology for investigating voltage unbalance in distribution networks with renewable generation is presented. The sequence networks are derived from the original asymmetrical three-phase network, and then interconnected to study sequence voltages and unbalance propagation through the network. The approach enables to analyse the influence of line impedance, load demand and network topology on voltage unbalance caused by distributed generation in the network. The critical factors which impact the unbalance severity and the propagation mode are also identified. The approach is validated by comparing calculated sequence voltages with the results obtained by phase voltage-based methodology