Plasma proteomic associations with genetics and health in the UK Biobank.

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Comorbid obesity and history of diabetes are independently associated with poorer treatment response to biologics at 6 months: A prospective analysis in Corrona Psoriasis Registry.

BACKGROUND: Psoriasis is associated with comorbid systemic metabolic disease. OBJECTIVE: To assess possible associations of comorbid obesity, history of diabetes, hypertension, and hyperlipidemia with response to biologic treatment at 6 months among patients in CorEvitas' Psoriasis Registry. METHODS: Participants included 2924 patients initiating biologic therapy (tumour necrosis factor inhibitors [TNFi], interleukin [IL]-17i, IL-12/23i, or IL-23i) with baseline and 6-month follow-up visits available. Logistic regressions resulted in adjusted odd ratios (OR) and 95% confidence intervals (CI) for achievement of response in select outcomes for those with obesity and history of diabetes, hypertension, and hyperlipidemia relative to those without each. RESULTS: Overall, obesity reduced by 25% to 30% odds of achieving PASI75 (OR, 0.75; 95% CI, 0.64-0.88) and PASI90 (OR, 0.70; 95% CI, 0.59-0.81). History of diabetes reduced odds of achieving PASI75 by 31% (OR, 0.69; 95% CI, 0.56-0.85) and PASI90 by 21% (OR, 0.79; 95% CI, 0.63-0.98). Obesity was associated with lower response to TNFi and IL-17i classes. Independent of obesity, diabetes was associated with poorer outcomes when on IL-17i therapy and hypertension, to a lesser extent, when on the TNFi class. No significant associations were found in the hyperlipidemia group. LIMITATIONS: The study assessed only short-term effectiveness and small sample sizes limited the power to detect differences. CONCLUSION: Assessment of comorbid disease burden is important for improved likelihoods of achieving treatment response with biologics.

Prospective cohort study of psoriatic arthritis risk in patients with psoriasis in a real-world psoriasis registry.

BACKGROUND: The characteristics that predict the onset of psoriatic arthritis (PsA) among patients with psoriasis (PsO) may inform diagnosis and treatment. OBJECTIVE: To develop a model to predict the 2-year risk of developing PsA among patients with PsO. METHODS: This was a prospective cohort study of patients in the CorEvitas Psoriasis Registry without PsA at enrollment and with 24-month follow-up. Unregularized and regularized logistic regression models were developed and tested using descriptive variables to predict dermatologist-identified PsA at 24 months. Model performance was compared using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. RESULTS: A total of 1489 patients were included. Nine unique predictive models were developed and tested. The optimal model, including Psoriasis Epidemiology Screening Tool (PEST), body mass index (BMI), modified Rheumatic Disease Comorbidity Index, work status, alcohol use, and patient-reported fatigue, predicted the onset of PsA within 24 months (AUC = 68.9%, sensitivity = 82.9%, specificity = 48.8%). A parsimonious model including PEST and BMI had similar performance (AUC = 68.8%; sensitivity = 92.7%, specificity = 36.5%). LIMITATIONS: PsA misclassification bias by dermatologists. CONCLUSION: PEST and BMI were important factors in predicting the development of PsA in patients with PsO over 2 years and thereby foundational for future PsA risk model development.

Combining statistics from two national complex surveys to estimate injury rates per hour exposed and variance by activity in the USA.

BACKGROUND: A common issue in descriptive injury epidemiology is that in order to calculate injury rates that account for the time spent in an activity, both injury cases and exposure time of specific activities need to be collected. In reality, few national surveys have this capacity. To address this issue, we combined statistics from two different national complex surveys as inputs for the numerator and denominator to estimate injury rate, accounting for the time spent in specific activities and included a procedure to estimate variance using the combined surveys. METHODS: The 2010 National Health Interview Survey (NHIS) was used to quantify injuries, and the 2010 American Time Use Survey (ATUS) was used to quantify time of exposure to specific activities. The injury rate was estimated by dividing the average number of injuries (from NHIS) by average exposure hours (from ATUS), both measured for specific activities. The variance was calculated using the 'delta method', a general method for variance estimation with complex surveys. RESULTS: Among the five types of injuries examined, 'sport and exercise' had the highest rate (12.64 injuries per 100 000 h), followed by 'working around house/yard' (6.14), driving/riding a motor vehicle (2.98), working (1.45) and sleeping/resting/eating/drinking (0.23). The results show a ranking of injury rate by activity quite different from estimates using population as the denominator. CONCLUSIONS: Our approach produces an estimate of injury risk which includes activity exposure time and may more reliably reflect the underlying injury risks, offering an alternative method for injury surveillance and research.

Work in multiple jobs and the risk of injury in the US working population.

OBJECTIVES: We compared the risk of injury for multiple job holders (MJHs) with that for single job holders (SJHs). METHODS: We used information from the National Health Interview Survey for the years 1997 through 2011 to estimate the rate of multiple job holding in the United States and compared characteristics and rates of self-reported injury (work and nonwork) for SJHs versus MJHs. RESULTS: Approximately 8.4% of those employed reported working more than 1 job in the week before the interview. The rate of work and nonwork injury episodes per 100 employed workers was higher for MJHs than for SJHs (4.2; 95% confidence interval [CI] = 3.5, 4.8; vs 3.3; 95% CI = 3.1, 3.5 work injuries and 9.9; 95% CI = 8.9, 10.9; vs 7.4; 95% CI = 7.1, 7.6 nonwork injuries per 100 workers, respectively). When calculated per 100 full-time equivalents (P < .05), the rate ratio remained higher for MJHs. CONCLUSIONS: Our findings suggest that working in multiple jobs is associated with an increased risk of an injury, both at work and not at work, and should be considered in injury surveillance.

Differences in time use and activity patterns when adding a second job: implications for health and safety in the United States.

OBJECTIVES: We compared work and lifestyle activities for workers who work in 1 job with those who work in multiple jobs during a 1-week period. METHODS: We used information from the 2003-2011 American Time Use Survey to classify workers into 6 work groups based on whether they were a single (SJH) or multiple (MJH) job holder and whether they worked their primary, other, multiple, or no job on the diary day. RESULTS: The MJHs often worked 2 part-time jobs (20%), long weekly hours (27% worked 60+ hours), and on weekends. The MJHs working multiple jobs on the diary day averaged more than 2 additional work hours (2.25 weekday, 2.75 weekend day; P < .05), odd hours (more often between 5 pm and 7 am), with more work travel time (10 minutes weekday, 9 minutes weekend day; P < .05) and less sleep (-45 minutes weekday, -62 minutes weekend day; P < .05) and time for other household (P < .05) and leisure (P < .05) activities than SJHs. CONCLUSIONS: Because of long work hours, long daily commutes, multiple shifts, and less sleep and leisure time, MJHs may be at heightened risk of fatigue and injury.

A novel method for quantitation of AAV genome integrity using duplex digital PCR.

Recombinant adeno-associated virus (rAAV) vectors have become a reliable strategy for delivering gene therapies. As rAAV capsid content is known to be heterogeneous, methods for rAAV characterization are critical for assessing the efficacy and safety of drug products. Multiplex digital PCR (dPCR) has emerged as a popular molecular approach for characterizing capsid content due to its high level of throughput, accuracy, and replicability. Despite growing popularity, tools to accurately analyze multiplexed data are scarce. Here, we introduce a novel statistical model to estimate genome integrity from duplex dPCR assays. This work demonstrates that use of a Poisson-multinomial mixture distribution significantly improves the accuracy and quantifiable range of duplex dPCR assays over currently available models.

Cardiometabolic multimorbidity is common among patients with psoriasis and is associated with poorer outcomes compared to those without comorbidity.

BACKGROUND: Associations between cardiometabolic multimorbidity and response to therapy in psoriasis are unknown. OBJECTIVE: Determine the associations of multimorbidity with response to biologic treatment in psoriasis patients. METHODS: CorEvitas Psoriasis Registry participants who initiated biologic therapy and had 6-month follow-up were stratified by 0, 1, 2+ comorbidities (diabetes, hypertension, hyperlipidemia). Adjusted odds ratios (95% CIs) were calculated overall and separately by biologic class (TNFi, IL-17i, IL-12/23i + IL-23i), to assess the likelihood of achieving response for the 1 and 2+ groups vs. 0. RESULTS: Of 2,923 patients, 49.5%, 24.7% and 25.8% reported 0, 1 and 2+ comorbidities, respectively. Overall, likelihood of PASI75 was 18% (OR = 0.82; 95%CI: 0.67, 1.00) and 23% (OR = 0.77; 95%CI: 0.63, 0.96) lower in those with 1 and 2+ comorbidities, respectively, vs. 0. In those who initiated IL-17i, odds of PASI75 and PAS90 were 34% (OR = 0.66; 95%CI: 0.48-0.91) and 35% (OR = 0.65; 95%CI: 0.47-0.91) lower in the 2+ multimorbidity cohort. No significant associations were found among users of TNFi or IL-12/23i + IL-23i groups in the multimorbidity group. LIMITATIONS: Patients may not be representative of all psoriasis patients. CONCLUSION: Multimorbidity in psoriasis may decrease the likelihood of achieving treatment response to biologic therapy and should be considered when discussing treatment expectations with patients.

Assessing the change in disease severity based on depressive symptoms in real-world psoriasis patients.

Aim: To evaluate whether the presence of a history of depression hinders psoriasis response to systemic therapies and to delineate baseline characteristics of patients whose depressive symptoms improved on systemic treatment. Methods: We studied patients within the Corrona® Psoriasis Registry, a prospective, multicenter observational disease-based registry, that were enrolled through September 2018, comparing changes from enrollment to 12-month visit. Results: There was a statistically significant improvement in all disease characteristics and most patient-reported outcomes in patients reporting a history of depression and in those that did not while there was no statistically significant difference in the degree of change comparing these two cohorts. Patients who noted improvement in depressive symptoms had more severe baseline disease characteristics and reported overall worse baseline patient-reported outcomes. Conclusions: History of depression does not portend a differential response to systemic treatment. Patients with improvement in depressive symptoms had worse baseline characteristics.

The Decline of Son Preference and Rise of Gender Indifference in Taiwan Since 1990.

This study explores the change of married women's sex preference for children in Taiwan since 1990, finding that there was a substantial decline of son preference and rise of "gender indifference", defined as feeling indifferent about children's sex (as opposed to desiring an equal number of boys and girls, in which the sex of children is still a primary consideration). Results show that at the individual level female education was the strongest predictor for the preference; education was negatively associated with son preference and positively with gender indifference. Cohort difference was noticeable, too. Younger cohorts were better educated than older ones so that they were more neutral about the sex and less adherent to the traditional male preference; besides, from 1992 to 2002 there was a universal intra-cohort movement toward gender neutrality and away from son preference. When the younger cohorts gradually replaced the older ones as the main child bearers in the Taiwanese society, at the aggregate level son preference declined and gender indifference rose.

Association Between Sedentary Work and BMI in a U.S. National Longitudinal Survey.

INTRODUCTION: Technological advancements have made life and work more sedentary, and long hours of sitting are known to be associated with many health concerns. Several studies have reported an association between prolonged sitting time at work and weight gain, but the results are inconsistent. This study examined the relationship between sitting time at work and BMI using data from a large prospective cohort of U.S. men and women from 2002 to 2010. Initial analyses were performed in 2013, with additional analyses in 2014 and 2015. METHODS: The sample size at the base year (2002) was 5,285 and the age range 38-45 years. The outcome, BMI, was based on self-reported measures of height and weight. Estimates of workplace sitting time were linked from an external database (Occupational Information Network), and the occupation-wide rating for sitting time was linked to survey participants by occupation. Fixed-effects models controlling for time-invariant effects of all time-invariant characteristics were employed to examine the association, controlling for age, education, work hours, and hours of vigorous and light/moderate physical activities. RESULTS: Longer sitting time was significantly associated with higher BMI for the overall sample (ß = 0.054; p<0.05) and men (ß = 0.086; p<0.01). For women, the association was not statistically significant. CONCLUSIONS: The findings provide further support for initiatives to reduce workplace sitting time as a means of reducing the risk of weight gain and related health conditions.

Son Preference and Children's Housework: The Case of India.

We use a nationally representative survey of Indian households (NFHS-3) to conduct the first study that analyzes whether son preference is associated with girls bearing a larger burden of housework than boys. Housework is a non-negligible part of child labor in which around 60 % of children in our sample are engaged. The preference for male offspring is measured by a mother's ideal proportion of sons among her offspring. We show that when the ideal proportion increases from 0 to 1, the gap in the time spent on weekly housework for an average girl compared to that of a boy increases by 2.5 h. We conduct several robustness analyses. First, we estimate the main model separately by caste, religion, and family size. Second, we use a two-stage model to look at participation into housework (as well as other types of work) in addition to hours. Third, we use mother's fertility intentions as an alternative measure of son preference. The analysis confirms that stated differences in male preference translate in de facto differences in girl's treatment.

Does obesity contribute to non-fatal occupational injury? Evidence from the National Longitudinal Survey of Youth.

OBJECTIVES: The relationship between obesity and occupational injuries remains unclear in the literature due to limitations in study design and sample composition. To better assess the contribution of obesity to occupational injury, we used data from a nationally representative cohort, the National Longitudinal Survey of Youth 1979 (NLSY79) in 1988-2000. METHODS: We hypothesized that obesity contributes to workplace injury and tested the hypothesis using logistic regression with generalized estimating equations (GEE) and random-effects logistic regression. To ensure temporal precedence of obesity, we used the obesity level in each previous wave and examined its association with injury outcome in each wave from 1988-2000. Obesity was measured as body mass index (BMI) based on self-reported height and weight. RESULTS: The GEE analysis showed that obesity was associated with 25% higher odds of workplace injury [odds ratio (OR) 1.25, 95% confidence interval (95% CI) 1.12-1.39; P<0.001). The random-effects regression indicated that obese workers were associated with 29% higher odds of sustaining injuries than those of normal weight (OR 1.29, 95% CI 1.15-1.45; P<0.001). CONCLUSIONS: Obesity may predispose workers to work-related injury; further research is needed to elucidate the mechanisms.