Incomplete Penetrance of Population-Based Genetic Screening Results in Electronic Health Record

The clinical value of population-based genetic screening projects depends on the actions taken on the findings. The Healthy Nevada Project (HNP) is an all-comer genetic screening and research project based in northern Nevada. HNP participants with CDC Tier 1 findings of hereditary breast and ovarian cancer syndrome (HBOC), Lynch syndrome (LS), or familial hypercholesterolemia (FH) are notified and provided with genetic counseling. However, the HNP subsequently takes a “hands-off” approach: it is the responsibility of notified participants to share their findings with their healthcare providers, and providers are expected to implement the recommended action plans. Thus, the HNP presents an opportunity to evaluate the efficiency of participant and provider responses to notification of important genetic findings, using electronic health records (EHRs) at Renown Health (a large regional hospital in northern Nevada). Out of 520 HNP participants with findings, we identified 250 participants who were notified of their findings and who had an EHR. 107 of these participants responded to a survey, with 76 (71%) indicating that they had shared their findings with their healthcare providers. However, a sufficiently specific genetic diagnosis appeared in the EHRs and problem lists of only 22 and 10%, respectively, of participants without prior knowledge. Furthermore, review of participant EHRs provided evidence of possible relevant changes in clinical care for only a handful of participants. Up to 19% of participants would have benefited from earlier screening due to prior presentation of their condition. These results suggest that continuous support for both participants and their providers is necessary to maximize the benefit of population-based genetic screening. We recommend that genetic screening projects require participants’ consent to directly document their genetic findings in their EHRs. Additionally, we recommend that they provide healthcare providers with ongoing training regarding documentation of findings and with clinical decision support regarding subsequent care.

SARS-CoV-2 test positivity rate in Reno, Nevada: association with PM2.5 during the 2020 wildfire smoke events in the western United States

BACKGROUND

Air pollution has been linked to increased susceptibility to SARS-CoV-2. Thus, it has been suggested that wildfire smoke events may exacerbate the COVID-19 pandemic.

OBJECTIVES

Our goal was to examine whether wildfire smoke from the 2020 wildfires in the western United States was associated with an increased rate of SARS-CoV-2 infections in Reno, Nevada.

METHODS

We conducted a time-series analysis using generalized additive models to examine the relationship between the SARS-CoV-2 test positivity rate at a large regional hospital in Reno and ambient PM2.5 from 15 May to 20 Oct 2020.

RESULTS

We found that a 10 µg/m³ increase in the 7-day average PM2.5 concentration was associated with a 6.3% relative increase in the SARS-CoV-2 test positivity rate, with a 95% confidence interval (CI) of 2.5 to 10.3%. This corresponded to an estimated 17.7% (CI: 14.4-20.1%) increase in the number of cases during the time period most affected by wildfire smoke, from 16 Aug to 10 Oct.

SIGNIFICANCE

Wildfire smoke may have greatly increased the number of COVID-19 cases in Reno. Thus, our results substantiate the role of air pollution in exacerbating the pandemic and can help guide the development of public preparedness policies in areas affected by wildfire smoke, as wildfires are likely to coincide with the COVID-19 pandemic in 2021.

Acute associations between PM2.5 and ozone concentrations and asthma exacerbations among patients with and without allergic comorbidities

Acute effects of outdoor air pollution on asthma exacerbations may vary by asthma phenotype (allergic vs nonallergic). Associations of ambient PM_2.5 and ozone concentrations with acute asthma visits (office, urgent, emergency, and hospitalization) were investigated using electronic medical records. International Classification of Disease codes were used to identify asthmatics, and classify them based on the presence or absence of an allergic comorbidity in their medical records. Daily 24-h average PM_2.5, 8-h maximum ozone, and mean temperature were obtained from a centralized monitor. Using a time-stratified case-crossover approach, pollutant concentrations were modeled using moving averages and distributed lag nonlinear models (lag 0-6) to examine lag associations and nonlinear concentration-response. The adjusted odds ratios for a 10 µg/m³ increase in 3-day moving average (lag 0-2) PM_2.5 in the two-pollutant models among patients with and without allergic comorbidities were 1.10 (95% confidence interval [CI]: 1.07, 1.13) and 1.05 (95% CI: 1.02, 1.09), respectively; and for a 20 ppb increase in 3-day moving average (lag 0-2) ozone were 1.08 (95% CI: 1.02, 1.14) and 1.00 (95% CI: 0.95, 1.05), respectively. Estimated odds ratios among patients with allergic comorbidities were consistently higher across age, sex, and temperature categories. Asthmatics with an allergic comorbidity may be more susceptible to ambient PM_2.5 and ozone.

Particulate matter and emergency visits for asthma: a time-series study of their association in the presence and absence of wildfire smoke in Reno, Nevada, 2013-2018

BACKGROUND

Health risks due to particulate matter (PM) from wildfires may differ from risk due to PM from other sources. In places frequently subjected to wildfire smoke, such as Reno, Nevada, it is critical to determine whether wildfire PM poses unique risks. Our goal was to quantify the difference in the association of adverse asthma events with PM on days when wildfire smoke was present versus days when wildfire smoke was not present.

METHODS

We obtained counts of visits for asthma at emergency departments and urgent care centers from a large regional healthcare system in Reno for the years 2013-2018. We also obtained dates when wildfire smoke was present from the Washoe County Health District Air Quality Management Division. We then examined whether the presence of wildfire smoke modified the association of PM_2.5, PM_10-2.5, and PM₁₀ with asthma visits using generalized additive models. We improved on previous studies by excluding wildfire-smoke days where the PM concentration exceeded the maximum PM concentration on other days, thus accounting for possible nonlinearity in the association between PM concentration and asthma visits.

RESULTS

Air quality was affected by wildfire smoke on 188 days between 2013 and 2018. We found that the presence of wildfire smoke increased the association of a 5 μg/m³ increase in daily and three-day averages of PM_2.5 with asthma visits by 6.1% (95% confidence interval (CI): 2.1-10.3%) and 6.8% (CI: 1.2-12.7%), respectively. Similarly, the presence of wildfire smoke increased the association of a 5 μg/m³ increase in daily and three-day averages of PM₁₀ with asthma visits by 5.5% (CI: 2.5-8.6%) and 7.2% (CI: 2.6-12.0%), respectively. We did not observe any significant increases in association for PM_10-2.5 or for seven-day averages of PM_2.5 and PM₁₀.

CONCLUSIONS

Since we found significantly stronger associations of PM_2.5 and PM₁₀ with asthma visits when wildfire smoke was present, our results suggest that wildfire PM is more hazardous than non-wildfire PM for patients with asthma.

Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts

Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data.

Population-based association analyses of rare genetic variants with complex traits are limited by the availability of data from sufficiently large cohorts. Here, Cirulli et al. report gene-based collapsing analysis of exomes from 49,960 participants of the UK Biobank and 21,866 participants of the Healthy Nevada Project over a total of 4377 traits.

GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort

In this study, we perform a full genome-wide association study (GWAS) to identify statistically significantly associated single nucleotide polymorphisms (SNPs) with three red blood cell (RBC) components and follow it with two independent PheWASs to examine associations between phenotypic data (case-control status of diagnoses or disease), significant SNPs, and RBC component levels. We first identified associations between the three RBC components: mean platelet volume (MPV), mean corpuscular volume (MCV), and platelet counts (PC), and the genotypes of approximately 500,000 SNPs on the Illumina Infimum DNA Human OmniExpress-24 BeadChip using a single cohort of 4,673 Northern Nevadans. Twenty-one SNPs in five major genomic regions were found to be statistically significantly associated with MPV, two regions with MCV, and one region with PC, with p<5x10^-8. Twenty-nine SNPs and nine chromosomal regions were identified in 30 previous GWASs, with effect sizes of similar magnitude and direction as found in our cohort. The two strongest associations were SNP rs1354034 with MPV (p = 2.4x10^-13) and rs855791 with MCV (p = 5.2x10^-12). We then examined possible associations between these significant SNPs and incidence of 1,488 phenotype groups mapped from International Classification of Disease version 9 and 10 (ICD9 and ICD10) codes collected in the extensive electronic health record (EHR) database associated with Healthy Nevada Project consented participants. Further leveraging data collected in the EHR, we performed an additional PheWAS to identify associations between continuous red blood cell (RBC) component measures and incidence of specific diagnoses. The first PheWAS illuminated whether SNPs associated with RBC components in our cohort were linked with other hematologic phenotypic diagnoses or diagnoses of other nature. Although no SNPs from our GWAS were identified as strongly associated to other phenotypic components, a number of associations were identified with p-values ranging between 1x10^-3 and 1x10^-4 with traits such as respiratory failure, sleep disorders, hypoglycemia, hyperglyceridemia, GERD and IBS. The second PheWAS examined possible phenotypic predictors of abnormal RBC component measures: a number of hematologic phenotypes such as thrombocytopenia, anemias, hemoglobinopathies and pancytopenia were found to be strongly associated to RBC component measures; additional phenotypes such as (morbid) obesity, malaise and fatigue, alcoholism, and cirrhosis were also identified to be possible predictors of RBC component measures.

A Classification of Alternative Lifestyle Groups

The study of alternative lifestyle groups has been based largely on anecdotal material. Recently, more systematic empirical research has led to the development of a number of classification systems. Four such systems from British, American and Australian social scientists are critically evaluated in the light of suggested criteria, and none of these are found to be adequate in a field research situation. A new classification is developed, which meets all the criteria, and which enhances rather than hinders research. Finally, from extensive Australian and New Zealand participant observation research data, some general characteristics are described for groups fitting into each category.

Search for pi(0)-->nu(mu)nu(mu) decays in the LSND detector

We observe a net beam excess of 8.7+/-6.3(stat)+/-2.4(syst) events, above 160 MeV, resulting from the charged-current reaction of nu(micro) and/or nu;(mu) on C and H in the LSND detector. No beam-related muon background is expected in this energy regime. Within an analysis framework of pi(0)-->nu(mu)nu;(mu), we set a direct upper limit for this branching ratio of Gamma(pi(0)-->nu(mu)nu;(mu))/Gamma(pi(0)-->all)<1.6 x 10(-6) at 90% confidence level.