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Article ; Online: Individual variation in contagious yawning susceptibility is highly stable and largely unexplained by empathy or other known factors.

Alex J Bartholomew / Elizabeth T Cirulli

PLoS ONE, Vol 9, Iss 3, p e

2014 Volume 91773

Abstract: The contagious aspect of yawning is a well-known phenomenon that exhibits variation in the human population. Despite the observed variation, few studies have addressed its intra-individual reliability or the factors modulating differences in the ... ...

Abstract	The contagious aspect of yawning is a well-known phenomenon that exhibits variation in the human population. Despite the observed variation, few studies have addressed its intra-individual reliability or the factors modulating differences in the susceptibility of healthy volunteers. Due to its obvious biological basis and impairment in diseases like autism and schizophrenia, a better understanding of this trait could lead to novel insights into these conditions and the general biological functioning of humans. We administered 328 participants a 3-minute yawning video stimulus, a cognitive battery, and a comprehensive questionnaire that included measures of empathy, emotional contagion, circadian energy rhythms, and sleepiness. Individual contagious yawning measurements were found to be highly stable across testing sessions, both in a lab setting and if administered remotely online, confirming that certain healthy individuals are less susceptible to contagious yawns than are others. Additionally, most individuals who failed to contagiously yawn in our study were not simply suppressing their reaction, as they reported not even feeling like yawning in response to the stimulus. In contrast to previous studies indicating that empathy, time of day, or intelligence may influence contagious yawning susceptibility, we found no influence of these variables once accounting for the age of the participant. Participants were less likely to show contagious yawning as their age increased, even when restricting to ages of less than 40 years. However, age was only able to explain 8% of the variability in the contagious yawn response. The vast majority of the variability in this extremely stable trait remained unexplained, suggesting that studies of its inheritance are warranted.
Keywords	Medicine ; R ; Science ; Q
Subject code	150
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Factors affecting pitch discrimination performance in a cohort of extensively phenotyped healthy volunteers

Lauren M. Smith / Alex J. Bartholomew / Lauren E. Burnham / Barbara Tillmann / Elizabeth T. Cirulli

Scientific Reports, Vol 7, Iss 1, Pp 1-

2017 Volume 9

Abstract: Abstract Despite efforts to characterize the different aspects of musical abilities in humans, many elements of this complex area remain unknown. Musical abilities are known to be associated with factors like intelligence, training, and sex, but a ... ...

Abstract	Abstract Despite efforts to characterize the different aspects of musical abilities in humans, many elements of this complex area remain unknown. Musical abilities are known to be associated with factors like intelligence, training, and sex, but a comprehensive evaluation of the simultaneous impact of multiple factors has not yet been performed. Here, we assessed 918 healthy volunteers for pitch discrimination abilities—their ability to tell two tones close in pitch apart. We identified the minimal threshold that the participants could detect, and we found that better performance was associated with higher intelligence, East Asian ancestry, male sex, younger age, formal music training–especially before age 6–and English as the native language. All these factors remained significant when controlling for the others, with general intelligence, musical training, and male sex having the biggest impacts. We also performed a small GWAS and gene-based collapsing analysis, identifying no significant associations. Future genetic studies of musical abilities should involve large sample sizes and an unbiased genome-wide approach, with the factors highlighted here included as important covariates.
Keywords	Medicine ; R ; Science ; Q
Subject code	780
Language	English
Publishing date	2017-11-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Analysis of Genetic and Non-Genetic Factors Influencing Timing and Time Perception.

Alex J Bartholomew / Warren H Meck / Elizabeth T Cirulli

PLoS ONE, Vol 10, Iss 12, p e

2015 Volume 0143873

Abstract: Performance on different psychophysical tasks measuring the sense of time indicates a large amount of individual variation in the accuracy and precision of timing in the hundredths of milliseconds-to-minutes range. Quantifying factors with an influence ... ...

Abstract	Performance on different psychophysical tasks measuring the sense of time indicates a large amount of individual variation in the accuracy and precision of timing in the hundredths of milliseconds-to-minutes range. Quantifying factors with an influence on timing is essential to isolating a biological (genetic) contribution to the perception and estimation of time. In the largest timing study to date, 647 participants completed a duration-discrimination task in the sub-second range and a time-production task in the supra-second range. We confirm the stability of a participant's time sense across multiple sessions and substantiate a modest sex difference on time production. Moreover, we demonstrate a strong correlation between performance on a standardized cognitive battery and performance in both duration-discrimination and time-production tasks; we further show that performance is uncorrelated with age after controlling for general intelligence. Additionally, we find an effect of ethnicity on time sense, with African Americans and possibly Hispanics in our cohort differing in accuracy and precision from other ethnic groups. Finally, a preliminary genome-wide association and exome chip study was performed on 148 of the participants, ruling out the possibility for a single common variant or groups of low-frequency coding variants within a single gene to explain more than ~18% of the variation in the sense of time.
Keywords	Medicine ; R ; Science ; Q
Subject code	150
Language	English
Publishing date	2015-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Individual Differences in Scotopic Visual Acuity and Contrast Sensitivity

Alex J Bartholomew / Eleonora M Lad / Dingcai Cao / Michael Bach / Elizabeth T Cirulli

PLoS ONE, Vol 11, Iss 2, p e

Genetic and Non-Genetic Influences.

2016 Volume 0148192

Abstract: Despite the large amount of variation found in the night (scotopic) vision capabilities of healthy volunteers, little effort has been made to characterize this variation and factors, genetic and non-genetic, that influence it. In the largest population ... ...

Abstract	Despite the large amount of variation found in the night (scotopic) vision capabilities of healthy volunteers, little effort has been made to characterize this variation and factors, genetic and non-genetic, that influence it. In the largest population of healthy observers measured for scotopic visual acuity (VA) and contrast sensitivity (CS) to date, we quantified the effect of a range of variables on visual performance. We found that young volunteers with excellent photopic vision exhibit great variation in their scotopic VA and CS, and this variation is reliable from one testing session to the next. We additionally identified that factors such as Circadian preference, iris color, astigmatism, depression, sex and education have no significant impact on scotopic visual function. We confirmed previous work showing that the amount of time spent on the vision test influences performance and that laser eye surgery results in worse scotopic vision. We also showed a significant effect of intelligence and photopic visual performance on scotopic VA and CS, but all of these variables collectively explain <30% of the variation in scotopic vision. The wide variation seen in young healthy volunteers with excellent photopic vision, the high test-retest agreement, and the vast majority of the variation in scotopic vision remaining unexplained by obvious non-genetic factors suggests a strong genetic component. Our preliminary genome-wide association study (GWAS) of 106 participants ruled out any common genetic variants of very large effect and paves the way for future, larger genetic studies of scotopic vision.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2016-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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

Elizabeth T. Cirulli / Simon White / Robert W. Read / Gai Elhanan / William J. Metcalf / Francisco Tanudjaja / Donna M. Fath / Efren Sandoval / Magnus Isaksson / Karen A. Schlauch / Joseph J. Grzymski / James T. Lu / Nicole L. Washington

Nature Communications, Vol 11, Iss 1, Pp 1-

2020 Volume 10

Abstract: 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 ... ...

Abstract	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.
Keywords	Science ; Q
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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

Nature Communications, Vol 11, Iss 1, Pp 1-

2020 Volume 10

Abstract	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.
Keywords	Science ; Q
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Acetaminophen (Paracetamol) Use Modifies the Sulfation of Sex Hormones

Isaac V. Cohen / Elizabeth T. Cirulli / Matthew W. Mitchell / Thomas J. Jonsson / James Yu / Naisha Shah / Tim D. Spector / Lining Guo / J. Craig Venter / Amalio Telenti

EBioMedicine, Vol 28, Iss C, Pp 316-

2018 Volume 323

Abstract: Background: Acetaminophen (paracetamol) is one of the most common medications used for management of pain in the world. There is lack of consensus about the mechanism of action, and concern about the possibility of adverse effects on reproductive health. ...

Abstract	Background: Acetaminophen (paracetamol) is one of the most common medications used for management of pain in the world. There is lack of consensus about the mechanism of action, and concern about the possibility of adverse effects on reproductive health. Methods: We first established the metabolome profile that characterizes use of acetaminophen, and we subsequently trained and tested a model that identified metabolomic differences across samples from 455 individuals with and without acetaminophen use. We validated the findings in a European ancestry adult twin cohort of 1880 individuals (TwinsUK), and in a study of 1235 individuals of African American and Hispanic ancestry. We used genomics to elucidate the mechanisms targeted by acetaminophen. Findings: We identified a distinctive pattern of depletion of sulfated sex hormones with use of acetaminophen across all populations. We used a Mendelian randomization approach to characterize the role of Sulfotransferase Family 2A Member 1 (SULT2A1) as the site of the interaction. Although CYP3A7-CYP3A51P variants also modified levels of some sulfated sex hormones, only acetaminophen use phenocopied the effect of genetic variants of SULT2A1. Overall, acetaminophen use, age, gender and SULT2A1 and CYP3A7-CYP3A51P genetic variants are key determinants of variation in levels of sulfated sex hormones in blood. The effect of taking acetaminophen on sulfated sex hormones was roughly equivalent to the effect of 35 years of aging. Interpretation: These findings raise concerns of the impact of acetaminophen use on hormonal homeostasis. In addition, it modifies views on the mechanism of action of acetaminophen in pain management as sulfated sex hormones can function as neurosteroids and modify nociceptive thresholds.
Keywords	Metabolome ; Mendelian randomization ; Sufotransferases ; sult2a1 ; Medicine ; R ; Medicine (General) ; R5-920
Language	English
Publishing date	2018-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An unsupervised learning approach to identify novel signatures of health and disease from multimodal data

Genome Medicine, Vol 12, Iss 1, Pp 1-

2020 Volume 14

Abstract: Abstract Background Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease ... ...

Abstract	Abstract Background Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease signatures. Methods We collected 1385 data features from diverse modalities, including metabolome, microbiome, genetics, and advanced imaging, from 1253 individuals and from a longitudinal validation cohort of 1083 individuals. We utilized a combination of unsupervised machine learning methods to identify multimodal biomarker signatures of health and disease risk. Results Our method identified a set of cardiometabolic biomarkers that goes beyond standard clinical biomarkers. Stratification of individuals based on the signatures of these biomarkers identified distinct subsets of individuals with similar health statuses. Subset membership was a better predictor for diabetes than established clinical biomarkers such as glucose, insulin resistance, and body mass index. The novel biomarkers in the diabetes signature included 1-stearoyl-2-dihomo-linolenoyl-GPC and 1-(1-enyl-palmitoyl)-2-oleoyl-GPC. Another metabolite, cinnamoylglycine, was identified as a potential biomarker for both gut microbiome health and lean mass percentage. We identified potential early signatures for hypertension and a poor metabolic health outcome. Additionally, we found novel associations between a uremic toxin, p-cresol sulfate, and the abundance of the microbiome genera Intestinimonas and an unclassified genus in the Erysipelotrichaceae family. Conclusions Our methodology and results demonstrate the potential of multimodal data integration, from the identification of novel biomarker signatures to a data-driven stratification of individuals into disease subtypes and stages—an essential step towards personalized, preventative health risk assessment.
Keywords	Multimodal ; Preventative medicine ; Metabolomics ; Cardiometabolic syndrome ; Unsupervised machine learning ; Network analysis ; Medicine ; R ; Genetics ; QH426-470
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility

Irene V. van Blokland / Pauline Lanting / Anil P. S. Ori / Judith M. Vonk / Robert C. A. Warmerdam / Johanna C. Herkert / Floranne Boulogne / Annique Claringbould / Esteban A. Lopera-Maya / Meike Bartels / Jouke-Jan Hottenga / Andrea Ganna / Juha Karjalainen / Lifelines COVID-19 cohort study / The COVID-19 Host Genetics Initiative / Caroline Hayward / Chloe Fawns-Ritchie / Archie Campbell / David Porteous /

Elizabeth T. Cirulli / Kelly M. Schiabor Barrett / Stephen Riffle / Alexandre Bolze / Simon White / Francisco Tanudjaja / Xueqing Wang / Jimmy M. Ramirez / Yan Wei Lim / James T. Lu / Nicole L. Washington / Eco J. C. de Geus / Patrick Deelen / H. Marike Boezen / Lude H. Franke

PLoS ONE, Vol 16, Iss

2021 Volume 8

Abstract: Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported ... ...

Abstract	Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

Irene V van Blokland / Pauline Lanting / Anil P S Ori / Judith M Vonk / Robert C A Warmerdam / Johanna C Herkert / Floranne Boulogne / Annique Claringbould / Esteban A Lopera-Maya / Meike Bartels / Jouke-Jan Hottenga / Andrea Ganna / Juha Karjalainen / Lifelines COVID-19 cohort study / COVID-19 Host Genetics Initiative / Caroline Hayward / Chloe Fawns-Ritchie / Archie Campbell / David Porteous /

Elizabeth T Cirulli / Kelly M Schiabor Barrett / Stephen Riffle / Alexandre Bolze / Simon White / Francisco Tanudjaja / Xueqing Wang / Jimmy M Ramirez / Yan Wei Lim / James T Lu / Nicole L Washington / Eco J C de Geus / Patrick Deelen / H Marike Boezen / Lude H Franke

PLoS ONE, Vol 16, Iss 8, p e

2021 Volume 0255402

Abstract	Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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