Large Epidemiological Cohort Research Articles

Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults.

Previous studies investigating environmental and behavioral drivers of chronic disease have often had limited temporal and spatial data coverage. Smartphone-based digital phenotyping mitigates the limitations of these studies by using intensive data collection schemes that take advantage of the widespread use of smartphones while allowing for less burdensome data collection and longer follow-up periods. In addition, smartphone apps can be programmed to conduct daily or intraday surveys on health behaviors and psychological well-being. The aim of this study was to investigate the feasibility and scalability of embedding smartphone-based digital phenotyping in large epidemiological cohorts by examining participant adherence to a smartphone-based data collection protocol in 2 ongoing nationwide prospective cohort studies. Participants (N=2394) of the Beiwe Substudy of the Nurses' Health Study 3 and Growing Up Today Study were followed over 1 year. During this time, they completed questionnaires every 10 days delivered via the Beiwe smartphone app covering topics such as emotions, stress and enjoyment, physical activity, access to green spaces, pets, diet (vegetables, meats, beverages, nuts and dairy, and fruits), sleep, and sitting. These questionnaires aimed to measure participants' key health behaviors to combine them with objectively assessed high-resolution GPS and accelerometer data provided by participants during the same period. Between July 2021 and June 2023, we received 11.1 TB of GPS and accelerometer data from 2394 participants and 23,682 survey responses. The average follow-up time for each participant was 214 (SD 148) days. During this period, participants provided an average of 14.8 (SD 5.9) valid hours of GPS data and 13.2 (SD 4.8) valid hours of accelerometer data. Using a 10-hour cutoff, we found that 51.46% (1232/2394) and 53.23% (1274/2394) of participants had >50% of valid data collection days for GPS and accelerometer data, respectively. In addition, each participant submitted an average of 10 (SD 11) surveys during the same period, with a mean response rate of 36% across all surveys (SD 17%; median 41%). After initial processing of GPS and accelerometer data, we also found that participants spent an average of 14.6 (SD 7.5) hours per day at home and 1.6 (SD 1.6) hours per day on trips. We also recorded an average of 1046 (SD 1029) steps per day. In this study, smartphone-based digital phenotyping was used to collect intensive longitudinal data on lifestyle and behavioral factors in 2 well-established prospective cohorts. Our assessment of adherence to smartphone-based data collection protocols over 1 year suggests that adherence in our study was either higher or similar to most previous studies with shorter follow-up periods and smaller sample sizes. Our efforts resulted in a large dataset on health behaviors that can be linked to spatial datasets to examine environmental and behavioral drivers of chronic disease.

Baseline characteristics of SARS-CoV-2 vaccine non-responders in a large population-based sample.

Studies indicate that individuals with chronic conditions and specific baseline characteristics may not mount a robust humoral antibody response to SARS-CoV-2 vaccines. In this paper, we used data from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a longitudinal state-wide seroprevalence program that has enrolled more than 90,000 participants, to evaluate the role of chronic diseases as the potential risk factors of non-response to SARS-CoV-2 vaccines in a large epidemiologic cohort. A participant needed to complete an online survey and a blood draw to test for SARS-CoV-2 circulating plasma antibodies at four-time points spaced at least three months apart. Chronic disease predictors of vaccine non-response are evaluated using logistic regression with non-response as the outcome and each chronic disease + age as the predictors. As of April 24, 2023, 18,240 participants met the inclusion criteria; 0.58% (N = 105) of these are non-responders. Adjusting for age, our results show that participants with self-reported immunocompromised status, kidney disease, cancer, and "other" non-specified comorbidity were 15.43, 5.11, 2.59, and 3.13 times more likely to fail to mount a complete response to a vaccine, respectively. Furthermore, having two or more chronic diseases doubled the prevalence of non-response. Consistent with smaller targeted studies, a large epidemiologic cohort bears the same conclusion and demonstrates immunocompromised, cancer, kidney disease, and the number of diseases are associated with vaccine non-response. This study suggests that those individuals, with chronic diseases with the potential to affect their immune system response, may need increased doses or repeated doses of COVID-19 vaccines to develop a protective antibody level.

Abstract P291: Understanding Participant Perspectives Towards the Formation of a National Participant Advisory Board Within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study: A Qualitative Study

Introduction: While participant advisory boards (PABs) are common among public health initiatives and clinical trials, they are less common among national, epidemiologic cohort studies. PABs could add value to researchers and participants alike, but their formation and functioning in this context is less understood. We aimed to elicit the perspectives of participants from the national REasons for Geographic and Racial Differences in Stroke (REGARDS) Study towards the formation of a PAB, which can inform future efforts to form one for this cohort study and others like it. Methods: REGARDS is a national prospective cohort study that enrolled >30,000 Black and White community-dwelling adults aged ≥45 years from 48 states 2003-2007. Enrollment and follow-up is ongoing and done through mail and telephone. We used a convenience sampling approach to recruit from a subset of participants who responded to a newsletter about joining a PAB. Participants completed a one-on-one telephone or Zoom-based interview with study staff following a semi-structured interview guide. Interviews were recorded and professionally transcribed. Data were organized with NVivo software. Informed by the Cargo and Mercer’s Health Equity Research Practice Framework for Academic-Community Partnerships, we conducted a thematic analysis. Each transcript was independently coded by two team members, then reconciled by a third. Major themes and subthemes were identified. Results: The 18 participants had a median age of 69 years, 67% were women, 39% were Black, and 78% had a college degree or higher. Overall, participants were enthusiastic about the PAB and were inclined to meet as a group regularly via Zoom or telephone. Four key themes emerged: (1) The PAB should form and function with a core set of principles, including: trust, diversity, mutual respect, and accountability; of these, diversity was most important; (2) The PAB should not only inform studies (i.e. research questions, methodology), but also assist with the dissemination of science to diverse networks; (3) A formal process is required to form and maintain the PAB, as well as keeping members engaged; (4) Core values influenced participants’ willingness to serve on the PAB; they included internal motivation, the desire to translate knowledge into action, and social and environmental justice. Conclusion: This study highlights a willingness of participants in large epidemiologic cohort to participate in a PAB. Our results can inform the formation of a PAB in the REGARDS Study, and may be important for other observational cohorts interested in including participants in an advisory capacity.

Validity and reliability of an app-based medical device to empower individuals in evaluating their physical capacities.

Cardiorespiratory fitness and muscle strength are valid markers of health and strong predictors of mortality and morbidity. The tests used to measure these variables require in-person visits with specialized equipment and trained personnel-leading to organizational constraints both for patients and hospitals, and making them difficult to implement at a large scale. In this context, technologies embedded in smartphones offer new opportunities to develop remote tests. This study aimed to test the validity and reliability of MediEval, a newly developed app-based medical device that allows individuals to perform the 6-minute walk test (6MWT) and the 30-second sit-to-stand (30s-STS) test on their own using GPS signal and camera detection with a skeleton extraction algorithm. A total of 53 healthy adults performed the two tests in three different sessions to determine the intra- and inter-day reproducibility. Test validity was assessed by comparing the results obtained from the app to gold standard measures. Pearson correlations and concordance correlation coefficients, the relative measurement error, intraclass correlation coefficients, the standard error of measure and the minimal detectable change were computed for each test.s. The results revealed high to excellent validity of the app in comparison to gold standards (ρ = 0.84 for the 6MWT and ρ = 0.99 for the 30s-STS test) with low relative measurement error. The mean differences between the app and the gold standard measures were 8.96m for the 6MWT and 0.28 repetition for the 30s-STS test. Both tests had good test-retest reliability (ICCs = 0.77). The minimal detectable changes were respectively 97.56 meters for the 6MWT and 7.37 repetitions for the 30s-STS test. The MediEval medical device proposes valid and reproducible measures of the 6MWT and the 30s-STS test. This device holds promise for monitoring the physical activity of large epidemiologic cohorts while refining patient experience and improving the scalability of the healthcare system. Considering minimal detectable change values, it may be important to ask participants to perform several tests and average them to improve accuracy. Future studies in clinical context are needed to evaluate the responsiveness and the smallest detectable changes of the device for specific populations with chronic diseases.

PERSIAN Eye Cohort Study (PECS): Design, Methodology.

To report the study protocol, methodology and latest enrollment data of a large epidemiological multi-central eye cohort named PERSIAN Eye Cohort Study (PECS), originating from the ongoing PERSIAN Cohort Study, to investigate the distribution of ophthalmic disorders in different regions and ethnicities of Iran, and determine their associations with various exposures of ophthalmic and non-ophthalmic nature. A central committee designed the study and equipped six chosen centers (Khameneh, Some'e Sara, Hoveizeh, Yazd, Rafsanjan and Zahedan). A focal point in each center conducted the study under close supervision of the central committee. This ongoing study was launched in 2014. Out of 65,580 eligible participants of the PERSIAN Cohort, 48,618 individuals aged 35-70 have been enrolled in the PECS (response rate: 74.13%) until June 2021. Slit lamp and fundus photography were performed for 28,702 (59.03%) and 27,437 (56.43%) individuals, respectively. This large epidemiological multi-central eye cohort can improve our epidemiological knowledge of the prevalent ophthalmic disorders in different regions and ethnicities of Iran, and determine their associations with various exposures of ophthalmic and non-ophthalmic nature. This will be very useful for future planned nationwide and global interventions.

Metagenomics of the Gut Microbiome in Parkinson's Disease: Prodromal Changes.

Prior studies on the gut microbiome in Parkinson's disease (PD) have yielded conflicting results, and few studies have focused on prodromal (premotor) PD or used shotgun metagenomic profiling to assess microbial functional potential. We conducted a nested case-control study within 2 large epidemiological cohorts to examine the role of the gut microbiome in PD. We profiled the fecal metagenomes of 420 participants in the Nurses' Health Study and the Health Professionals Follow-up Study with recent onset PD (N = 75), with features of prodromal PD (N = 101), controls with constipation (N = 113), and healthy controls (N = 131) to identify microbial taxonomic and functional features associated with PD and features suggestive of prodromal PD. Omnibus and feature-wise analyses identified bacterial species and pathways associated with prodromal and recently onset PD. We observed depletion of several strict anaerobes associated with reduced inflammation among participants with PD or features of prodromal PD. A microbiome-based classifier had moderate accuracy (area under the curve [AUC] = 0.76 for species and 0.74 for pathways) to discriminate between recently onset PD cases and controls. These taxonomic shifts corresponded with functional shifts indicative of carbohydrate source preference. Similar, but less marked, changes were observed in participants with features of prodromal PD, in both microbial features and functions. PD and features of prodromal PD were associated with similar changes in the gut microbiome. These findings suggest that changes in the microbiome could represent novel biomarkers for the earliest phases of PD. ANN NEUROL 2023;94:486-501.

Association of Polyunsaturated Fatty Acids and Clinical Progression in Patients With ALS: Post Hoc Analysis of the EMPOWER Trial.

Polyunsaturated fatty acids (PUFAs) have neuroprotective and anti-inflammatory effects and could be beneficial in amyotrophic lateral sclerosis (ALS). Higher dietary intake and plasma levels of PUFAs, in particular alpha-linolenic acid (ALA), have been associated with a lower risk of ALS in large epidemiologic cohort studies, but data on disease progression in patients with ALS are sparse. We examined whether plasma levels of ALA and other PUFAs contributed to predicting survival time and functional decline in patients with ALS. We conducted a study among participants in the EMPOWER clinical trial who had plasma samples collected at the time of randomization that were available for fatty acid analyses. Plasma fatty acids were measured using gas chromatography. We used Cox proportional hazards models and linear regression to evaluate the association of individual fatty acids with risk of death and joint rank test score of functional decline and survival. Fatty acid analyses were conducted in 449 participants. The mean (SD) age of these participants at baseline was 57.5 (10.7) years, and 293 (65.3%) were men; 126 (28.1%) died during follow-up. Higher ALA levels were associated with lower risk of death (age-adjusted and sex-adjusted hazard ratio comparing highest vs lowest quartile 0.50, 95% CI 0.29-0.86, p-trend = 0.041) and higher joint rank test score (difference in score according to 1 SD increase 10.7, 95% CI 0.2-21.1, p = 0.045), consistent with a slower functional decline. The estimates remained similar in analyses adjusted for body mass index, race/ethnicity, symptom duration, site of onset, riluzole use, family history of ALS, predicted upright slow vital capacity, and treatment group. Higher levels of the n-3 fatty acid eicosapentaenoic acid and the n-6 fatty acid linoleic acid were associated with a lower risk of death during follow-up. Higher levels of ALA were associated with longer survival and slower functional decline in patients with ALS. These results suggest that ALA may have a favorable effect on disease progression in patients with ALS.

Automated Radiographic Measurements of Knee Osteoarthritis.

Herewith, we report the development of Orthopedic Digital Image Analysis (ODIA) software that is developed to obtain quantitative measurements of knee osteoarthritis (OA) radiographs automatically. Manual segmentation and measurement of OA parameters currently hamper large-cohort analyses, and therefore, automated and reproducible methods are a valuable addition in OA research. This study aims to test the automated ODIA measurements and compare them with available manual Knee Imaging Digital Analysis (KIDA) measurements as comparison. This study included data from the CHECK (Cohort Hip and Cohort Knee) initiative, a prospective multicentre cohort study in the Netherlands with 1,002 participants. Knee radiographs obtained at baseline of the CHECK cohort were included and mean medial/lateral joint space width (JSW), minimal JSW, joint line convergence angle (JLCA), eminence heights, and subchondral bone intensities were compared between ODIA and KIDA. Of the potential 2,004 radiographs, 1,743 were included for analyses. Poor intraclass correlation coefficients (ICCs) were reported for the JLCA (0.422) and minimal JSW (0.299). The mean medial and lateral JSW, eminence height, and subchondral bone intensities reported a moderate to good ICC (0.7 or higher). Discrepancies in JLCA and minimal JSW between the 2 methods were mostly a problem in the lateral tibia plateau. The current ODIA tool provides important measurements of OA parameters in an automated manner from standard radiographs of the knee. Given the automated and computerized methodology that has very high reproducibility, ODIA is suitable for large epidemiological cohorts with various follow-up time points to investigate structural progression, such as CHECK or the Osteoarthritis Initiative (OAI).

Examining ultrafine particle pollution and lung cancer risk in a large, diverse cohort.

8532 Background: Health effects associated with particles less than 2.5 μm in diameter (PM2.5) have been well studied, leading to the establishment of air quality standards and routine monitoring. Additionally, there is growing experimental evidence that ultrafine particles (UFPs), defined as particles less than 0.1µm in diameter, may adversely affect lung health, eliciting greater injury than larger particles due to deeper penetration into airways and longer retention in the lung parenchyma. Only two epidemiological studies have investigated this topic, finding no associations between ambient UFPs and respiratory mortality or overall lung cancer incidence respectively. Given the limited epidemiologic investigation of UFPs and lung cancer, we examined the association between airport-related UFPs and lung cancer incidence in a large, racially and ethnically diverse cohort. Methods: We estimated airport-related UFP exposure for 71,387 participants of the Multiethnic Cohort, who lived within a 53 km×43 km grid area around the Los Angeles International Airport (LAX) from date of cohort entry (1993-1996) through December 31, 2013. Cox proportional hazards regression was used, with calendar month/year as the time variable, to examine associations between UFP exposure and lung cancer risk adjusting for demographics, lifetime smoking, neighborhood socioeconomic status, occupation and lifestyle factors. Subgroup analyses were conducted by racial and ethnic groups, lung cancer histology, and smoking status. Co-pollutant models were run to mutually adjust for other traffic-related air pollutants. Results: A per unit increase in the interquartile range (IQR) of airport-related UFP exposure was not associated with lung cancer risk overall [HR = 1.01, 95% CI: 0.97-1.05] or by race and ethnicity. UFP exposure was suggestive of a positive association with risk of lung squamous cell carcinoma (SCC) [HR per IQR = 1.08, 95% CI: 1.00-1.17]. No associations were observed for other histologies [Phet for histology = .05]. UFP exposure was associated with an increased SCC risk among current smokers [HR = 1.11, 95% CI: 1.01-1.22] but not among never or past smokers [Phet for smoking = 0.51]. Conclusions: This study suggests a possible association between airport-related UFP exposure and risk of SCC. These results may be explained by previous studies finding that UFPs activate genes involved in oxidative damage, TNF-α signaling via NF-κB, and secretion of inflammatory and cardiopulmonary disease biomarkers. These findings warrant further investigation in large epidemiologic cohorts.

0324 Protective and Risk Factors for Insomnia Over 5 Years in a Population-Based Sample of Adults

Abstract Introduction Insomnia is a major public health concern and one of the most prevalent health issues among adults. Identifying protective and risk factors for insomnia could help identify vulnerable populations and design public health interventions to prevent some adverse medical and mental health consequences. The study objective was to identify protective and risk factors for insomnia in a population-based sample of adults. Methods Data is from a large epidemiological cohort study on the natural course of insomnia conducted in Canada before the COVID-19 pandemic. Insomnia and potential protective and risk factors for insomnia were measured annually over 5 years with validated questionnaires (e.g., Insomnia Severity Index, Pittsburgh Sleep Quality Index, State-Trait Anxiety Inventory, Beck Depression Inventory, Perceived Stress Scale, Coping Inventory for Stressful Situations, Ford Insomnia Response to Stress Test, Arousal Predisposition Scale, Life Experiences Survey). Risk factors for insomnia were divided as predisposing or precipitating factors. Results From a cohort of 3,413 participants 1,709 adults were identified as good sleepers at baseline and were included in the analyses. A total of 202 people developed an insomnia syndrome during the 5-year follow-up. Using survival analysis for discrete events, the following variables were significant predisposing factors for insomnia: anxiety (HR=1.037; p=0.018), depression (HR=1.082; p< 0.001), perceived stress (HR=1.073; p< 0.001), number of negative life events (HR=1.478; p=0.02), perceived worse general health (HR=1.606; p=0.006), pain (HR=1.475; p=0.002), vulnerability to stress (HR=1.089; p< 0.001), and maladaptive emotional coping (HR=1.044; p< 0.001). The following variables were identified as precipitating factors for insomnia: loss of income (HR=1.346; p=0.03), increased anxiety (HR=1.070, p< 0.001), depression (HR=1.119; p< 0.001) and perceived stress (HR=1.083; p=0.001), decline in perceived general health (HR=2.061; p=0.006), and increased pain (HR=1.353; p=0.013). Physical activity was not a significant protective factor for insomnia (p=0.54). Conclusion These results provide new information that could be helpful to prevent the onset and chronicity of insomnia by targeting specific precipitating factors, and people with predisposing factors for insomnia. This is important as insomnia tends to be a persistent condition and is known to increase adverse medical and mental health outcomes. Support (if any) This study was funded by the Canadian Institutes of Health Research.

False Indications of Dose-Response Nonlinearity in Large Epidemiologic Cancer Radiation Cohort Studies; A Simulation Exercise.

This study explores the likely prevalence of false indications of dose-response nonlinearity in large epidemiologic cancer radiation cohort studies (A-bomb survivors, INWORKS, Techa River). Reasons: Increasing numbers of tests of nonlinearity are being made in studies. Hypothesized nonlinear dose-response models have been justified to policy makers by analyses that rely in part on isolated findings that could be statistical fluctuations. After removing dose nonlinearity (linearization) by adjusting person-years of observation at each dose category, indications of nonlinearity, necessarily false, were counted in 5,000 randomized replications of six datasets. The average frequency of any false positive for five indicators of nonlinearity tested against a linear null was roughly 25% in Monte Carlo simulations per study, consistent with binomial calculations, increasing to ∼50% within 6 studies assessed. Comparable frequencies were found using Akaike's information criterion (AIC) for model selection or multi-model averaging. False above-zero threshold doses were found more than 50% of the time, averaging to 0.05 Gy, consistent with findings in the 6 studies. Such bias, uncorrected, could distort meta-analyses of multiple studies, because meta-analyses can incorporate high P value findings. AIC-based correction for the extra threshold parameter lowered these false occurrences to 8 to 19%. Given the simulation rates, the possibility of false positives might be noted when isolated findings of nonlinearity are discussed in a regulatory context. When reporting a threshold dose with a P value > 0.05, it would be informative to note the expected high false prevalence rate due to bias.

Development and Validation of the Epidemiological Tattoo Assessment Tool to Assess Ink Exposure and Related Factors in Tattooed Populations for Medical Research: Cross-sectional Validation Study.

Tattooing, whose popularity is growing worldwide, is an invasive body art that involves the injection of chemical mixtures, the tattoo ink, into the upper layer of the dermis. Although these inks may contain environmental toxins, including known human carcinogens, their long-term health effects are poorly studied. To conduct the urgently required epidemiological studies on tattoos and their long-term health effects, a validated method for assessing the complex tattoo exposure is needed. We aimed to develop and validate the Epidemiological Tattoo Assessment Tool (EpiTAT), a questionnaire to self-assess tattoo ink exposure in tattooed populations suitable for application in large epidemiological cohort studies. One of 3 preliminary versions of the EpiTAT using one of the alternative tattoo measurement units hand surface, credit card, or body schemes was randomly filled in by tattooed volunteers in Lyon, France. To identify the most suitable unit of tattoo self-assessment, a validation study was conducted with the selected respondents (N=97) to compare the self-assessments of tattoo surface, color, and coverage with validation measurements made by trained study personnel. Intraclass correlation, the Kendall rank correlation, and 2-tailed t tests were used to statistically compare tattoo size, color area, and tattoo coverage separately for each questionnaire version. Participants' opinions on the alternative measurement units were also considered in the overall evaluation. For quality control of the validation measures, digital surface analysis of 62 photographs of selected tattoos was performed using Fiji/ImageJ. In general, the results revealed overestimation of self-assessed measures compared with validation measures (eg, mean tattooed body surface 1768, SD 1547, cm2 vs 930, SD 1047, cm2, respectively, for hand surface; P<.001) and validation measures compared with digital image analysis (mean individual tattoo surface 147, SD 303.9, cm2 vs 101, SD 154.7, cm2, respectively; P=.05). Although the measurement unit credit card yielded the most accurate measures for all variables of interest, it had a much lower completion rate (78/129, 60.5%) than hand surface (89/104, 85.6%) and body schemes (90/106, 84.9%). Hand surface measured total tattoo size more accurately than body schemes (absolute agreement intraclass correlation coefficient: 0.71 vs 0.64, respectively). The final version of the EpiTAT contains 21 items and uses hand surface as a visual unit of measurement. Likert scales are used to assess color and coverage as a proportion of the total tattoo area. The overestimation of tattoo size by self-reporting merits further research to identify potential influential factors or predictive patterns that could be considered when calculating exposure.

APOE alleles are associated with sex-specific structural differences in brain regions affected in Alzheimer's disease and related dementia.

Alzheimer's disease is marked by intracellular tau aggregates in the medial temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we examined codependent structural variations between the MTL's most vulnerable structure, the hippocampus (HC), and the DN at subregion resolution in individuals with Alzheimer's disease and related dementia (ADRD). By leveraging the power of the approximately 40,000 participants of the UK Biobank cohort, we assessed impacts from the protective APOE ɛ2 and the deleterious APOE ɛ4 Alzheimer's disease alleles on these structural relationships. We demonstrate ɛ2 and ɛ4 genotype effects on the inter-individual expression of HC-DN co-variation structural patterns at the population level. Across these HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix's fimbria, and their cortical partners related to ADRD risk. Analyses of the rich phenotypic profiles in the UK Biobank cohort further revealed male-specific HC-DN associations with air pollution and female-specific associations with cardiovascular traits. We also showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our structural, genetic, and phenotypic analyses in this large epidemiological cohort reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex and link APOE alleles to inter-individual brain structural differences indicative of ADRD familial risk.

Loss of PTEN Expression, PIK3CA Mutations, and Breast Cancer Survival in the Nurses' Health Studies.

The relationships between PTEN loss and/or PIK3CA mutation and breast cancer prognosis remain controversial. We aim to examine the associations in large epidemiologic cohorts. We followed women with invasive breast cancer from the Nurses' Health Studies with available data on tumor PTEN expression (n = 4,111) and PIK3CA mutation (n = 2,930). PTEN expression was evaluated by IHC and digitally scored (0%-100%). Pyrosequencing of six hotspot mutations of PIK3CA was performed. We found loss of PTEN expression (≤10%) occurred in 17% of cases, and PIK3CA mutations were detected in 11% of cases. After adjusting for clinical and lifestyle factors, PTEN loss was not associated with worse breast cancer-specific mortality among all samples [HR, 0.85; 95% confidence intervals (CI), 0.71-1.03] or among estrogen receptor (ER)-positive tumors (HR, 0.99; 95% CI, 0.79-1.24). However, among ER-negative tumors, PTEN loss was associated with lower breast cancer-specific mortality (HR, 0.68; 95% CI, 0.48-0.95). PIK3CA mutation was not strongly associated with breast cancer-specific mortality (HR, 0.89; 95% CI, 0.67-1.17). Compared with tumors without PTEN loss and without PIK3CA mutation, those with alterations (n = 540) were not at higher risk (HR, 1.07; 95% CI, 0.86-1.34). However, women with both PTEN loss and PIK3CA mutation (n = 38) were at an increased risk of breast cancer-specific mortality (HR, 1.65; 95% CI, 0.83-3.26). In this large epidemiologic study, the PTEN-mortality association was more pronounced for ER-negative tumors, and the joint PTEN loss and PIK3CA mutation may be associated with worse prognosis. Further studies with a larger sample of ER-negative tumors are needed to replicate our findings and elucidate underlying mechanisms.

Geomagnetic disturbances reduce heart rate variability in the Normative Aging Study

BackgroundSolar and geomagnetic activity (GA) have been linked to increased cardiovascular (CVD) events. We hypothesize that heart rate variability (HRV) may be the biological mechanism between increased CVD risk and intense geomagnetic disturbances (GMD). MethodsTo evaluate the impact of GA and intense GMD on HRV in 809 elderly men [age mean 74.5 (SD = 6.8)] enrolled in the Normative Aging Study (Greater Boston Area), we performed repeated-measures using mixed-effects regression models. We evaluated two HRV outcomes: the square root of the mean squared differences of successive normal-to-normal intervals (r-MSSD) and the standard deviation of normal-to-normal heartbeat intervals (SDNN) in milliseconds (ms). We also compared the associations between Kp and HRV in patients with and without comorbidities such as diabetes and coronary heart diseases (CHD). We used data on global planetary K-Index (Kp) from middle latitudes as a GA and GMD (>75th Kp) parameters from the National Oceanic and Atmospheric Agency's Space Weather Prediction Center. ResultsWe found a near immediate effect of continuous and higher Kp on reduced HRV for exposures up to 24 h prior to electrocardiogram recording. A 75th percentile increase in 15-hour Kp prior the examination was associated with a −14.7 ms change in r-MSSD (95 CI: −23.1, −6.3, p-value = 0.0007) and a −8.2 ms change in SDNN (95 CI: −13.9, −2.5, p-value = 0.006). The associations remained similar after adjusting the models for air pollutants over the exposure window prior to the event. In periods of intense GMD, the associations were stronger in patients with CHD and non-diabetes. ConclusionsThis is the first study to demonstrate the potential adverse effects of geomagnetic activity on reduced heart rate variability in a large epidemiologic cohort over an extended period, which may have important clinical implications among different populations.

MACHINE LEARNING FOR ASSOCIATION OF WEARABLE-SENSOR DERIVED GAIT MEASURES WITH WORSENING KNEE PAIN OVER 2-YEARS: THE MULTICENTER OSTEOARTHRITIS STUDY

Purpose: Altered gait is related to structural worsening of knee osteoarthritis (OA). However, it is not known if altered gait is associated with increased risk of pain worsening over time. We applied machine learning approaches to gait data collected in a large epidemiological cohort to identify markers of gait alterations in people with worsening knee pain over 2 years.

A method for remotely measuring physical function in large epidemiologic cohorts: Feasibility and validity of a video-guided sit-to-stand test.

Traditional measures of muscular strength require in-person visits, making administration in large epidemiologic cohorts difficult. This has left gaps in the literature regarding relationships between strength and long-term health outcomes. The aim of this study was to test the feasibility and validity of a video-led, self-administered 30-second sit-to-stand (STS) test in a sub-cohort of the U.S.-based Cancer Prevention Study-3. A video was created to guide participants through the STS test. Participants submitted self-reported scores (n = 1851), and optional video recordings of tests (n = 134). Two reviewers scored all video tests. Means and standard deviations (SD) were calculated for self-reported and video-observed scores. Mean differences (95% confidence intervals (CI)) and Spearman correlation coefficients between self-reported and observed scores were calculated, stratifying by demographic characteristics. Participants who uploaded a video reported 14.1 (SD = 3.5) stands, which was not significantly different from the number of stands achieved by the full cohort (13.9 (SD = 4.2), P-difference = 0.39). Self-reported and video-observed scores were highly correlated (ρ = 0.97, mean difference = 0.3, 95% CI = 0.1-0.5). There were no significant differences in correlations by sociodemographic factors (all P-differences ≥0.42). This study suggests that the self-administered, video-guided STS test may be appropriate for participants of varying ages, body sizes, and activity levels, and is feasible for implementation within large, longitudinal studies. This video-guided test would also be useful for remote adaptation of the STS test during the COVID-19 pandemic.

Abstract 14097: Pharmacometabolomic Profiling Of The General Population: Relation Of Active Metabolite Levels To Cardiovascular Risk Factor Control And Manifest Atherosclerosis

Introduction: The use of medications in the general population has increased over time. Information on active metabolite concentrations for common drugs in the general population is limited. Recent advances in metabolomic technologies have made high-throughput profiling of many active metabolites in large epidemiological cohorts increasingly feasible. Aim: 1. Prospective assessment of the proportion of measurable active metabolite levels of major drugs in the general population using mass spectrometry. 2. Relation of cardiovascular (CV) drugs with inadequate risk factor control and CV disease. Methods: Assessment of CV risk factors by coronary CT angiography and carotid ultrasound imaging in a large prospective cohort of 6,251 individuals randomly selected from the general population in Malmö, Sweden (age 50-64 years). Untargeted metabolomic profiling of fasting plasma was performed by Metabolon, USA in a random subset of 3,986 subjects. Results: Intake of at least one prescribed drug was reported in 1840 subjects (46%). Combination drugs were reported in 249 subjects (6%). The most common drug classes reported were lipid-lowering (n=369, 9% of which most were statins), beta blockers (n=307, 8%), ARB (n=272, 7%), and ACE inhibitors (268, 7%), followed by levothyroxine, CCB, antidepressants, glucocorticoids, PPI, antidiabetic, bronchodilators and diuretics. For major CV drugs, detectable active metabolite levels ranged from 54% (atorvastatin and enalapril) to 96% (metoprolol and metformin). Non-detectable levels of lipid-lowering, antihypertensive, and antidiabetic drugs were associated with higher LDL, cholesterol, BP and glucose, although only antidiabetic drugs were significant (p&lt;0.05). Non-detectable levels of lipid-lowering and antihypertensive drugs were also non-significantly associated with increased coronary calcium and carotid plaque. Conclusion: Our study provides an overview of the distribution of common drugs with detectable levels in a contemporary Swedish population. Pharmacometabolomic profiling revealed that non-measurable levels of common CV drugs were associated with lower risk factor control and non-significant trends towards more atherosclerotic disease by imaging in a substantial number of subjects.

Editors' Note: Guillain-Barré Syndrome in the Placebo and Active Arms of a COVID-19 Vaccine Clinical Trial

In “Guillain-Barré Syndrome in the Placebo and Active Arms of a COVID-19 Vaccine Clinical Trial,” Márquez Loza et al. presented a patient who developed the Guillain-Barré syndrome (GBS) after being vaccinated in a COVID-19 vaccine clinical trial and highlighted the fact that this should not be considered a postvaccination complication, given that, by chance alone, 900–2,200 people can be expected to develop GBS within 6 weeks of a 1-dose vaccine and 1,500–3,700 people can be expected to develop GBS within 10 weeks of a 2-dose vaccine. Willer comments that although vaccines can increase the risk of GBS because of antibody production, they can also decrease the risk of GBS because of infection prevention. On behalf of the authors, Amato agrees that vaccines can reduce the risk of postinfection GBS in general but notes that a large epidemiologic cohort study found no causal relationship between COVID-19 and GBS and no evidence of molecular mimicry between any SARS-CoV-2 proteins and axonal or myelin proteins in human nerves. Amato recommends performance of large-scale epidemiologic studies and meta-analyses to better understand the relationship between COVID-19 vaccination and GBS. In “Guillain-Barré Syndrome in the Placebo and Active Arms of a COVID-19 Vaccine Clinical Trial,” Márquez Loza et al. presented a patient who developed the Guillain-Barré syndrome (GBS) after being vaccinated in a COVID-19 vaccine clinical trial and highlighted the fact that this should not be considered a postvaccination complication, given that, by chance alone, 900–2,200 people can be expected to develop GBS within 6 weeks of a 1-dose vaccine and 1,500–3,700 people can be expected to develop GBS within 10 weeks of a 2-dose vaccine. Willer comments that although vaccines can increase the risk of GBS because of antibody production, they can also decrease the risk of GBS because of infection prevention. On behalf of the authors, Amato agrees that vaccines can reduce the risk of postinfection GBS in general but notes that a large epidemiologic cohort study found no causal relationship between COVID-19 and GBS and no evidence of molecular mimicry between any SARS-CoV-2 proteins and axonal or myelin proteins in human nerves. Amato recommends performance of large-scale epidemiologic studies and meta-analyses to better understand the relationship between COVID-19 vaccination and GBS.

Predictors of diagnostic stability in brief psychotic disorders: Findings from a 3-year longitudinal study.

Brief psychotic disorder (BPD) is a relatively uncommon and underexplored psychotic condition. Even though BPD has been related to a more favorable outcome than other schizophrenia spectrum disorders (SSD), current knowledge of its predictive factors remains scant. This study aimed to examine its prevalence and find early predictors of BPD diagnostic stability. SSD diagnosis following Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria was explored in a large epidemiological cohort (n=569) of non-affective first-episode psychosis (FEP) patients enrolled in a three-year longitudinal intervention program (PAFIP). Premorbid, sociodemographic, and clinical information was collected to characterize BPD patients and determine factors predictive of diagnostic stability. Multivariate analysis included predictors selected from clinical knowledge and also those that had achieved marginal significance (p≤0.1) in univariate analysis. A total of 59 patients enrolled in the PAFIP program (10.4% of the whole cohort) met DSM-IV criteria for BPD, of whom 40 completed the three-year follow-up. The temporal stability of BPD in our sample was as high as 40% (n=16). Transition from BPD to schizophrenia occurred in 37% (n=15) of patients. Fewer hallucinations at baseline and better insight independently significantly predicted BPD diagnostic stability over time. Our findings confirm that BPD is a clinical condition with moderate-to-low temporal stability and demonstrate that approximately two-thirds of FEP individuals experiencing BPD will develop a long-lasting psychotic disorder during follow-up, mainly schizophrenia.