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Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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134 hot topic(s) found with the query "Behavior"

Personalized mood prediction from patterns of behavior collected with smartphones
B Balliu et al, NPJ DIgital Medicine, February 28, 2024 (Posted: Mar 03, 2024 10AM)

From the abstract: "We report high-quality longitudinal validated assessments of depressive mood from computerized adaptive testing paired with continuous digital assessments of behavior from smartphone sensors for up to 40 weeks on 183 individuals experiencing mild to severe symptoms of depression. We apply a combination of cubic spline interpolation and idiographic models to generate individualized predictions of future mood from the digital behavioral phenotypes, achieving high prediction accuracy of depression severity up to three weeks in advance (R2 =?80%) and a 65.7% reduction in the prediction error. "

Distilling causality between physical activity traits and obesity via Mendelian randomization.
Zhe Wang et al. Commun Med (Lond) 2023 11 (1) 173 (Posted: Dec 02, 2023 8AM)

From the abstract: "Whether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed. This MR study highlights the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI."

Risk perception and intended behavior change after uninformative genetic results for adult-onset hereditary conditions in unselected patients.
Nandana D Rao et al. Eur J Hum Genet 2023 9 (Posted: Sep 27, 2023 8AM)

From the abstract: "Overall, 2761 people received uninformative results and 1352 (49%) completed survey items. Respondents averaged 41 years old, 62% were female, and 56% were Non-Hispanic Asian. Results from the FACToR instrument showed mean (SD) scores of 0.92 (1.34), 7.63 (3.95), 1.65 (2.23), and 0.77 (1.50) for negative emotions, positive emotions, uncertainty, and privacy concerns, respectively, suggesting minimal psychosocial harms from genetic screening. Overall, 12.2% and 9.6% of survey respondents believed that their risk of cancer or heart disease, respectively, had changed after receiving their uninformative genetic screening results. Further, 8.5% of respondents planned to make healthcare changes and 9.1% other behavior changes. "

At-home wearables and machine learning sensitively capture disease progression in amyotrophic lateral sclerosis
AS Gupta et al, Nature Comm. August 21, 2023 (Posted: Aug 22, 2023 9AM)

We investigate the use of wearable sensors, worn on four limbs at home during natural behavior, to quantify motor function and disease progression in 376 individuals with amyotrophic lateral sclerosis. We use an analysis approach that automatically detects and characterizes submovements from passively collected accelerometer data and produces a machine-learned severity score for each limb that is independent of clinical ratings. We show that this approach produces scores that progress faster than the gold standard Amyotrophic Lateral Sclerosis Functional Rating Scale.

What Is Huntington Disease?
R Marcus, JAMA, August 21, 2023 (Posted: Aug 21, 2023 1PM)

Huntington disease is a rare genetic disease that affects movement, thinking, and behavior. Huntington disease results from an abnormal gene that damages cells in the brain. It is an autosomal dominant genetic disorder, meaning that individuals born to a parent with Huntington disease have a 50% chance of developing the disease. Rarely, patients with Huntington disease have a gene variant that developed spontaneously and was not inherited. Huntington disease affects about 11 to 14 people per 100?000 individuals in Europe and North America and is less common in Africa and East Asia.

Genomic testing for rare disease diagnosis—where are we now, and where should we be heading? The reflections of a behavioural scientist
C Lewis, EJHG, August 1, 2023 (Posted: Aug 01, 2023 9AM)

Much work has been done by behavioral scientists over recent years to understand patients’ and parents’ motivations for undergoing genomic testing. Findings highlight patients’ and parents’ desire: for a diagnosis to access treatments, for access to clinical trials and/or disease-specific screening; to receive a clear prognosis and information about recurrence risk; to understand the etiology of the condition and receive a reason “why” it occurred; to gain relief from guilt, for example, that it was not caused by something the mother did during her pregnancy (a concern I frequently come across); to gain legitimacy for the patient’s behavior and/or appearance; and to enable them the opportunity to connect with others through support groups and social media.

Epidemic modelling of monitoring public behavior using surveys during pandemic-induced lockdowns.
Andreas Koher et al. Commun Med (Lond) 2023 6 (1) 80 (Posted: Jun 11, 2023 8AM)

Implementing a lockdown for disease mitigation is a balancing act: Non-pharmaceutical interventions can reduce disease transmission significantly, but interventions also have considerable societal costs. Therefore, decision-makers need near real-time information to calibrate the level of restrictions. Here, we find that, unlike mobility, self-reported contacts decreased significantly in all regions before the nation-wide implementation of non-pharmaceutical interventions and improved predicting future hospitalizations compared to mobility data. A detailed analysis of contact types indicates that contact with friends and strangers outperforms contact with colleagues and family members (outside the household) on the same prediction task.

Wearables and AI better predict the progression of muscular dystrophy
Nature Medicine, January 20, 2023 (Posted: Jan 21, 2023 6AM)

Clinical trials in neurological diseases often involve subjective, qualitative endpoints, such ‘by eye’ observations of movement. We developed an artificial intelligence–based method to analyze natural daily behavior data from people with Duchenne muscular dystrophy, using machine-learning algorithms to accurately predict their personal disease trajectories better than conventional clinical assessments.

Wearable full-body motion tracking of activities of daily living predicts disease trajectory in Duchenne muscular dystrophy.
Ricotti Valeria et al. Nature medicine 2023 1 (Posted: Jan 20, 2023 6AM)

Artificial intelligence has the potential to revolutionize healthcare, yet clinical trials in neurological diseases continue to rely on subjective, semiquantitative and motivation-dependent endpoints for drug development. To overcome this limitation, we collected a digital readout of whole-body movement behavior of patients with Duchenne muscular dystrophy (DMD) (n?=?21) and age-matched controls (n?=?17).

Clinical Cancer and Direct-to-Consumer Genetic Test Result-Sharing Behavior: Findings from HINTS 2020
S Makhnoon et al, J Per Med, December 21, 2022 (Posted: Dec 22, 2022 9AM)

Using nationally representative population-based data collected from the Health Information National Trends Survey, we identified the prevalence and factors associated with genetic test result-sharing behavior for high-risk cancer tests, genetic health risk tests, and ancestry tests. Overall, 68.4% of those who underwent high-risk cancer genetic testing shared their results with FDRs, whereas 89.9% shared with HCP/GCs. Women were nine times more likely than men to share, and those with a personal history of cancer were less likely to share with HCP/GCs. Of those tested for genetic health risk, 66.5% shared with HCP/GCs, 38.7% with FDRs, 66.6% with a spouse/partner, 12.8% with a friend, and 14.1% did not share results with anyone.

Models of communication for polygenic scores and associated psychosocial and behavioral effects on recipients: A systematic review.
Wallingford Courtney K et al. Genetics in medicine : official journal of the American College of Medical Genetics 2022 11 (Posted: Nov 03, 2022 8AM)

In total, 28 articles, representing 17 studies in several disease settings were identified. There was limited consistency in PGS communication and evaluation/reporting of outcomes. Most studies (n = 14) presented risk in multiple ways (ie, numerically, verbally, and/or visually). Three studies provided personalized lifestyle advice and additional resources. Only 1 of 17 studies reported using behavior change theory to inform their PGS intervention. Our findings call for development of best communication practices and evidence-based interventions informed by behavior change theories.

Life expectancy changes since COVID-19
J Scholey et al, Nature Hum Behavior, October 17, 2022 (Posted: Oct 17, 2022 5PM)

We estimate life expectancy changes in 29 countries since 2020 (including most of Europe, the United States and Chile), attribute them to mortality changes by age group and compare them with historic life expectancy shocks. Our results show divergence in mortality impacts of the pandemic in 2021. While countries in western Europe experienced bounce backs from life expectancy losses of 2020, eastern Europe and the United States witnessed sustained and substantial life expectancy deficits.

The monkeypox virus is mutating. Are scientists worried?
M Koslov, Nature, October 5, 2022 (Posted: Oct 06, 2022 8AM)

In some samples, large chunks of the virus’s genome have disappeared — but understanding whether the mutations affect its behavior will be difficult. Although scientists aren’t alarmed, they are monitoring the situation carefully to understand why the alterations have appeared, and what they might mean for the global monkeypox outbreak. These mutations are a stark reminder that even poxviruses — which are DNA viruses that tend to evolve more slowly than RNA viruses, such as the SARS-CoV-2 coronavirus — will change over time.

Can Smartphones Help Predict Suicide?
E Barry, NY Times, September 30, 2022 (Posted: Oct 01, 2022 7AM)

In the field of mental health, few new areas generate as much excitement as machine learning, which uses computer algorithms to better predict human behavior. There is, at the same time, exploding interest in biosensors that can track a person’s mood in real time, factoring in music choices, social media posts, facial expression and vocal expression. A unique research project is tracking hundreds of people at risk for suicide, using data from smartphones and wearable biosensors to identify periods of high danger — and intervene.

Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation
KP Venkatesh et al, NPJ Digital Medicine, Sepetmber 22, 2022 (Posted: Sep 23, 2022 7AM)

Health digital twins are defined as virtual representations (“digital twin”) of patients (“physical twin”) that are generated from multimodal patient data, population data, and real-time updates on patient and environmental variables. With appropriate use, HDTs can model random perturbations on the digital twin to gain insight into the expected behavior of the physical twin—offering groundbreaking applications in precision medicine, clinical trials, and public health.

The Vasopressin 1a Receptor Antagonist SRX246 Reduces Aggressive Behavior in Huntington’s Disease
HT Mailbach et al, J Pers Medicine, September 22, 2022 (Posted: Sep 22, 2022 6AM)

Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.
Wang Zhe et al. Nature genetics 2022 9 (Posted: Sep 08, 2022 6AM)

Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training.

Can extended reality in the metaverse revolutionise health communication?
Plechatá Adéla et al. NPJ digital medicine 2022 9 (1) 132 (Posted: Sep 04, 2022 8AM)

In the metaverse, users will actively engage with 3D content using extended reality (XR). Such XR platforms can stimulate a revolution in health communication, moving from information-based to experience-based content. We outline three major application domains and describe how the XR affordances (presence, agency and embodiment) can improve healthy behavior by targeting the users’ threat and coping appraisal

When Silence Disrupts
RC Hunt et al, NEJM, August 24, 2022 (Posted: Aug 24, 2022 6PM)

A common assumption is that synonymous codon changes, so called because they do not alter the encoded amino acid sequence, are neutral genetic variants that have no effect on phenotype or genetic fitness. However, there is a mounting body of literature showing that synonymous variants influence protein biosynthesis and the biologic behavior of cells and underlie human disease.

A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust
N Shutz et al, NPJ Digital Medicine, August 16, 2022 (Posted: Aug 16, 2022 10AM)

We introduce and describe a zero-interaction digital exhaust: a set of 1268 digital measures that cover large parts of a person’s activity, behavior and physiology. Making this approach more inclusive of older adults, we base this set entirely on contactless, zero-interaction sensing technologies. Applying the resulting digital exhaust to real-world data, we then demonstrate the possibility to create multiple ageing relevant digital clinical outcome assessments. Paired with modern machine learning, we find these assessments to be surprisingly powerful and often on-par with mobile approaches

Genomic and transcriptomic determinants of response to neoadjuvant therapy in rectal cancer.
Chatila Walid K et al. Nature medicine 2022 8 (Posted: Aug 16, 2022 10AM)

To define correlates of response to neoadjuvant therapy, we analyzed genomic and transcriptomic profiles of 738 untreated rectal cancers. APC mutations were less frequent in the lower than in the middle and upper rectum, which could explain the more aggressive behavior of distal tumors. No somatic alterations had significant associations with response to neoadjuvant therapy in a treatment-agnostic manner, but KRAS mutations were associated with faster relapse in patients treated with neoadjuvant chemoradiation followed by consolidative chemotherapy. Overexpression of IGF2 and L1CAM was associated with decreased response to neoadjuvant therapy.

Animal Reservoirs—Where the Next SARS-CoV-2 Variant Could Arise
J Madhusoodanan, JAMA, August 3, 2022 (Posted: Aug 04, 2022 1PM)

As the virus jumps across species barriers, it also adapts to a range of different hosts, stockpiling mutations that can change its behavior, transmissibility, or ability to evade vaccines and immune defenses in as-yet-unknown ways. “What we might fear is a situation where, when things seem like they’re under control, we have a new variant that spreads fast, looks really different, and we don’t know where it came from.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer
J Byun et al, Nature Genetics, August 1, 2022 (Posted: Aug 01, 2022 11AM)

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity.

Impact of a Population Genomic Screening Program on Health Behaviors Related to Familial Hypercholesterolemia Risk Reduction.
Jones Laney K et al. Circulation. Genomic and precision medicine 2022 101161CIRCGEN121003549 (Posted: Jul 26, 2022 9AM)

We conducted a retrospective cohort study of MyCode participants with an FH risk variant beginning 2 years before disclosure until January 16, 2019. We analyzed lipid-lowering prescriptions (clinician behavior), medication adherence (participant behavior), and LDL (low-density lipoprotein) cholesterol levels (health outcome impact) pre- and post-disclosure. Data were collected from electronic health records and claims. Despite disclosure of an FH risk variant, nonprescribing and nonadherence to lipid-lowering therapy remained high. However, when clinicians intensified medication regimens and participants adhered to medications, lipid levels decreased.

Nongenetic Factors Associated With Psychotic Experiences Among UK Biobank Participants Exposome-Wide Analysis and Mendelian Randomization Analysis
BD Lin et al, JAMA Psychiatry, July 20, 2022 (Posted: Jul 20, 2022 0PM)

What are the factors associated with psychotic experiences? In this cohort study of 155?247 UK Biobank participants, exposome-wide association analysis yielded 148 correlates of psychotic experiences, with 36 independent associations further identified in the fully adjusted multivariable model. Mendelian randomization analyses of these 36 variables indicated a forward association with ever having experienced sexual assault and pleiotropy of risk-taking behavior and a reverse association with ever having experienced a physically violent crime, cannabis use, and worrying too long after embarrassment.

Convergence and Divergence of Rare Genetic Disorders on Brain Phenotypes: A Review.
Raznahan Armin et al. JAMA psychiatry 2022 6 (Posted: Jul 01, 2022 8AM)

Rare genetic disorders modulating gene expression—as exemplified by gene dosage disorders (GDDs)—represent a collectively common set of high-risk factors for neuropsychiatric illness. Research on GDDs is rapidly expanding because these variants have high effect sizes and a known genetic basis. Moreover, the prevalence of recurrent GDDs (encompassing aneuploidies and certain copy number variations) enables genetic-first phenotypic characterization of the same GDD across multiple individuals, thereby offering a unique window into genetic influences on the human brain and behavior.

Perspectives of diverse Spanish- and English-speaking patients on the clinical use of polygenic risk scores
SA Sukiel et al, Genetics in Medicine, April 5, 2022 (Posted: Apr 06, 2022 9AM)

Perceived utility of clinical PRS focused on the potential for personal health benefits, and most participants stated that high-risk results would prompt physician consultations and health behavior changes. There was little concern among participants about the limited predictive power of PRS for non-European populations. Barriers to uptake of PRS testing and adoption of PRS-related recommendations included socioeconomic factors, insurance status, race, ethnicity, language, and inadequate understanding of PRS.

Culturally adapting internet- and mobile-based health promotion interventions might not be worth the effort: a systematic review and meta-analysis
S Balci et al, NPJ Digital Medicine, March 23, 2022 (Posted: Mar 24, 2022 8AM)

Out of 9438 records, 13 randomized controlled trials (RCT) investigating culturally adapted health promotion IMI addressing healthy eating, physical activity, alcohol consumption, sexual health behavior, and smoking cessation included. From the included studies 10,747 participants were eligible. Culturally adapted IMI proved to be non-superior over active control conditions in short- (g?=?0.10, [95% CI -0.19 to 0.40]) and long-term (g?=?0.20, [95% CI -0.11 to 0.51]) in promoting health behavior. However, culturally adapted IMI for physical activity (k?=?3, N?=?296) compared to active controls yielded a beneficial effect in long-term (g?=?0.48, [95%CI 0.25 to 0.71]).

An Open Repository of Real-Time COVID-19 Indicators
A Reinhart et al, MEDRXIV, November 11, 2021 (Posted: Nov 12, 2021 7AM)

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID- 19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily.

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan
SA Arik et al,NPJ Digital Medicine, October 8, 2021 (Posted: Oct 09, 2021 7AM)

We present an international, prospective evaluation of our models’ performance across all states and counties in the USA and prefectures in Japan. Nationally, incident mean absolute percentage error (MAPE) for predicting COVID-19 associated deaths during prospective deployment remained consistently <8% (US) and <29% (Japan), while cumulative MAPE remained <2% (US) and <10% (Japan). We show that our models perform well even during periods of considerable change in population behavior, and are robust to demographic differences across different geographic locations. We further demonstrate that our framework provides meaningful explanatory insights with the models accurately adapting to local and national policy interventions.

Mental health: build predictive models to steer policy Combine economic, social and medical data to forecast need and design services to address the growing crisis.
JA Occhipinti et al, Nature, September 26, 2021 (Posted: Sep 27, 2021 7AM)

We argue that a systems-modelling approach should be used to tackle the mental-health challenge. Drawing together qualitative and quantitative evidence and data, models should capture changes triggered by the pandemic — such as education loss, job loss, domestic violence, social isolation, fear and uncertainty. Models should forecast demand for community mental-health services and acute care, including emergency-department presentations and psychiatric hospitalizations, as well as outcomes such as suicidal behavior.

Mendelian Randomization: Using Genetics to Study Behaviors and Environments that Cause Disease
CDC, August 2021 Brand (Posted: Sep 01, 2021 7AM)

An important part of public health research is looking at whether behaviors, environments, and other factors, which can sometimes be changed, make people more likely to get certain diseases. However, showing that these factors cause a specific disease presents challenges. Mendelian randomization studies examine how certain behaviors, environments, or other factors lead to specific health outcomes by looking at genetic differences that affect the way people’s bodies react to the behavior, environment, or other factors.

Governing Human Germline Editing Through Patent Law.
Sherkow Jacob S et al. JAMA 2021 8 (Posted: Aug 31, 2021 8AM)

Even though patents are not a perfect solution to the ethical challenges of germline editing, they are a useful supplement to many of the approaches currently available, especially given fractured international regulation. Patents present an opportunity to combine the tools of commercialization and ethical behavior in a manner not readily present in other fields. It is an opportunity that should not be wasted; the perfect should not be the enemy of the good.

The design, implementation, and effectiveness of intervention strategies aimed at improving genetic referral practices: a systematic review of the literature.
Morrow April et al. Genetics in medicine : official journal of the American College of Medical Genetics 2021 8 (Posted: Aug 25, 2021 8AM)

Genetic referral interventions are rarely informed by implementation and/or behavior change theories, limiting opportunities for learning across contexts. Retrospective coding has provided a suite of theoretically linked strategies, which may be useful for informing future efforts. Incorporating these strategies into clinical guidelines may facilitate operationalization within the system.

The mutation that helps Delta spread like wildfire- A key amino-acid change might underlie the coronavirus variant’s ferocious infectivity.
E Callaway, Nature, August 20, 2021 (Posted: Aug 20, 2021 1PM)

As the world grapples with the hyper-infectious Delta coronavirus variant, scientists are racing to understand the biological basis for its behavior. A slew of studies has highlighted an amino-acid change present in Delta that might contribute to its swift spread. Delta is at least 40% more transmissible than is the Alpha variant identified in the United Kingdom in late 2020, epidemiological studies suggest.

A worldwide assessment of changes in adherence to COVID-19 protective behaviours and hypothesized pandemic fatigue
A Petherick et al, Nat Hum Behavior, August 3, 2021 (Posted: Aug 04, 2021 11AM)

Our results show that changes in adherence were empirically meaningful and geographically widespread. While a low-cost and habituating behaviour (mask wearing) exhibited a linear rise in adherence, high-cost and sensitizing behaviours (physical distancing) declined, but this decline decelerated over time, with small rebounds seen in later months. Reductions in adherence to physical distancing showed little difference across societal groups, but were less intense in countries with high interpersonal trust. Alternative underlying mechanisms and policy implications are discussed.

Breast cancer polygenic risk scores: a 12-month prospective study of patient reported outcomes and risk management behavior
T Yanes et al, GIM, August 2, 2021 (Posted: Aug 02, 2021 4PM)

Of the 208 participants, 165 (79%) received their PRS. Among receivers, there were no changes in anxiety or distress following testing. However, compared to women with a low PRS, those with a high PRS reported greater genetic testing–specific distress, perceived risk, decisional regret, and less genetic testing–positive response. At 12 months, breast screening and uptake of risk-reducing strategies were consistent with current guidelines of breast cancer risk management.

Coffee Consumption and Incident Tachyarrhythmias- Reported Behavior, Mendelian Randomization, and Their Interactions
EJ Kim et al, JAMA Int Med, July 2021 (Posted: Jul 20, 2021 7AM)

In this population-based community cohort study of more than 300?000 participants, each additional daily cup of coffee was associated with a 3% reduced risk of developing an arrhythmia; these associations were not significantly modified by genetic variants that affect caffeine metabolism. A mendelian randomization study leveraging did not reveal evidence that caffeine consumption increases the risk of incident arrhythmias.

Networks of SARS-CoV-2 transmission
M Cevik et al, Science, July 9, 2021 (Posted: Jul 09, 2021 8AM)

The focus of COVID-19 response strategies has often been on behavior change as a primary means of decreasing contact networks and thus transmission chains. However, contact patterns are driven, in large part, by socioeconomic inequities and structural racism and are nonmodifiable at the individual level in the absence of specific support.

Understanding, explaining, and utilizing medical artificial intelligence
R Cadario et al, Nat Hum Behavior, June 29, 2021 (Posted: Jun 30, 2021 7AM)

Medical artificial intelligence is cost-effective and scalable and often outperforms human providers, yet people are reluctant to use it. We show that resistance to the utilization of medical artificial intelligence is driven by both the subjective difficulty of understanding algorithms (the perception that they are a ‘black box’) and by an illusory subjective understanding of human medical decision-making.

Resource profile and user guide of the Polygenic Index Repository
J Becker et al, Nature Human Behavior, June 17, 2021 (Posted: Jun 18, 2021 6AM)

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies—some not previously published—from multiple data sources.

Maternal prenatal gut microbiota composition predicts child behaviour
SL Dawson et al, Ebiomedicine, June 4, 2021 (Posted: Jun 06, 2021 7AM)

We found evidence that the alpha diversity of the maternal fecal microbiota during the third trimester of pregnancy predicts child internalizing behavior at two years of age (-2·74, (-4·71, -0·78), p = 0·01 (Wald test), R2=0·07).

A global analysis of the impact of COVID-19 stay-at-home restrictions on crime
AE Nivette et al, Nature Human Behavior, June 3, 2021 (Posted: Jun 04, 2021 11AM)

A global database of COVID-19 vaccinations
E Mathiou et al, Nature Hum Behavior, May 10, 2021 (Posted: May 11, 2021 7AM)

We present the Our World in Data COVID-19 vaccination dataset, a global public dataset that tracks the scale and rate of the vaccine rollout across the world. This dataset is updated regularly and includes data on the total number of vaccinations administered, first and second doses administered, daily vaccination rates and population-adjusted coverage for all countries for which data are available (169 countries as of 7 April 2021).

Failure of genetic therapies for Huntington’s devastates community- Hopes were high for drugs designed to lower levels of a mutant protein, but development has stalled.
D Kwon, Nature News, May 5, 2021 (Posted: May 06, 2021 0PM)

Two pharmaceutical companies have halted clinical trials of gene-targeting therapies for Huntington’s disease (HD), following the drugs’ disappointing performance. Researchers had hoped that the treatments — known as antisense oligonucleotides (ASOs) — would be a game changer for HD, an incurable genetic condition that affects cognition, behavior and movement. But back-to-back announcements have dealt a crushing blow to those affected by the disease.

Machine learning prediction of blood alcohol concentration: a digital signature of smart-breathalyzer behavior
K Aschbacher et al, NPJ Digital Medicine, April 20, 2021 (Posted: Apr 21, 2021 7AM)

We developed a digital phenotype of long-term smart-breathalyzer behavior to predict individuals’ breath alcohol concentration (BrAC) levels trained on data from a smart breathalyzer. We analyzed roughly one million datapoints from 33,452 users of a commercial smart-breathalyzer device, collected between 2013 and 2017. For validation, we analyzed the associations between state-level observed smart-breathalyzer BrAC levels and impaired-driving motor vehicle death rates.

Symptom-level modelling unravels the shared genetic architecture of anxiety and depression
JG Thorp et al, Nature Human Behavior, April 15, 2021 (Posted: Apr 19, 2021 10AM)

Measuring voluntary and policy-induced social distancing behavior during the COVID-19 pandemic.
Yan Youpei et al. Proceedings of the National Academy of Sciences of the United States of America 2021 4 (16) (Posted: Apr 07, 2021 1PM)

Americans showed nontrivial voluntary behavioral changes in response to COVID-19 risk. The magnitude of voluntary response likely would have increased with increasing cases. Stay-at-home orders overlapped and replaced the voluntary response to cases. However, mandates kept more people home earlier in the epidemic, and epidemiological processes are sensitive to the magnitude and timing of behavioral changes.

Socioeconomic impacts of COVID-19 in low-income countries
A Josephson, et al, Nature Human Behavior, March 31, 2021 (Posted: Apr 02, 2021 8AM)

We used longitudinal household survey data from Ethiopia, Malawi, Nigeria and Uganda, originating from pre-COVID-19 face-to-face household surveys plus phone surveys implemented during the pandemic. We estimate that 256 million individuals—77% of the population—live in households that have lost income during the pandemic. Attempts to cope with this loss are exacerbated by food insecurity and an inability to access medicine and staple foods.

Leveraging risk communication science across US federal agencies
WMP Klein et al, Nature Human Behavior, March 18, 2021 (Posted: Mar 20, 2021 8AM)

Many US federal agencies apply principles from risk communication science across a wide variety of hazards. In so doing, they identify key research and practice gaps that, if addressed, could help better serve the nation’s communities and greatly enhance practice, research, and policy development.

Large socio-economic, geographic and demographic disparities exist in exposure to school closures
Z Parolin et al, Nature Human Behavior, March 2021 (Posted: Mar 20, 2021 7AM)

We introduce a U.S. School Closure and Distance Learning Database that tracks in-person visits across more than 100,000 schools throughout 2020. The database, which we make publicly accessible and update monthly, describes year-over-year change in in-person visits to each school throughout 2020 to estimate whether the school is engaged in distance learning. Our findings reveal that school closures from September to December 2020 were more common in schools with lower third-grade math scores and higher shares of students from racial/ethnic minorities, who experience homelessness, have limited English proficiency and are eligible for free/reduced-price school lunches.

Assessing the quality of mobile applications in chronic disease management: a scoping review
P Agarwal et all, NPJ Digital Medicine, March 10, 2021 (Posted: Mar 12, 2021 8AM)

This study highlights the significant variation in quality criteria employed for the assessment of mobile health apps. Future methods for app evaluation will benefit from approaches that leverage the best evidence regarding the clinical impact and behavior change mechanisms while more directly reflecting patient needs when evaluating the quality of apps.

Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA
NS Loomba et al, ature Human Behavior, February 5, 2021 (Posted: Feb 06, 2021 7AM)

A randomized controlled trial conducted in the US and UK shows that #COVID19 vaccine misinformation is associated with a decline in intent of accepting the vaccine by >6 percentage points in both countries.

Upping uptake of COVID contact tracing apps
S Toussaert, Nature Human Behavior, January 2021 (Posted: Jan 28, 2021 9AM)

To contain the COVID-19 pandemic, many countries around the world rushed to develop digital contact tracing apps. However, the low rates of app installation have undermined the efficacy of such tools. A new study shines light on potential barriers to adoption, as well as levers that could be used to increase uptake.

Identification of Suicide Attempt Risk Factors in a National US Survey Using Machine Learning.
García de la Garza Ángel et al. JAMA psychiatry 2021 Jan (Posted: Jan 25, 2021 11AM)

This study used a large, nationally representative longitudinal survey of US adults to create a suicide attempt model addressing risk factors of suicide. The most important factors included previous suicidal ideation or behavior, feeling downhearted, doing activities less carefully or accomplishing less because of emotional problems, younger age, lower educational achievement, and recent financial crisis.

From the Exposome to the Socioexposome in COVID-19 Research—A Call for More Multidisciplinary Research
S Koch et al, JAMA Network Open, December 29, 2020 (Posted: Dec 31, 2020 9AM)

A socioexposome approach combines expertise in the fields of genomics, environmental exposures, and health behavior sciences with the expertise pooled in social sciences.7 With this multidisciplinary framework, researchers can situate and contextualize natural science data and findings across the individual, local, and global scales, rendering a full picture of the interplay among biological disease pathways and social and environmental forces.

Comparison of Knowledge and Information-Seeking Behavior After General COVID-19 Public Health Messages and Messages Tailored for Black and Latinx Communities : A Randomized Controlled Trial.
Alsan Marcella et al. Annals of internal medicine 2020 Dec (Posted: Dec 29, 2020 10AM)

This is an RCT to determine whether physician-delivered prevention messages affect knowledge and information-seeking behavior of Black and Latinx individuals and whether this differs according to the race/ethnicity of the physician and tailored content. Physician-delivered messages increased knowledge of COVID-19 symptoms and prevention methods for Black and Latinx respondents. Desire for information increased with race-concordant messages for Black but not Latinx respondents.

Cell phone mobility data and manifold learning: Insights into population behavior during the COVID-19 pandemic
R Levin et al, MEDRXIV, November 16, 2020 (Posted: Nov 18, 2020 8AM)

Ranking the effectiveness of worldwide COVID-19 government interventions
N Haug et al, Nature Human Behavior, November 16, 2020 (Posted: Nov 17, 2020 8AM)

Here we quantify the impact of 6,068?hierarchically coded NPIs implemented in 79?territories on the effective reproduction number, Rt, of COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools.

Real-time, interactive website for US-county-level COVID-19 event risk assessment
A Chande et al, Nature Human Behavior, November 9, 2020 (Posted: Nov 13, 2020 8AM)

To provide real-time, geolocalized risk information, we developed an interactive online dashboard that estimates the risk that at least one individual with SARS-CoV-2 is present in gatherings of different sizes in the United States. The website combines documented case reports at the county level with ascertainment bias information obtained via population-wide serological surveys to estimate real-time circulating, per-capita infection rates.

Neighbourhood income and physical distancing during the COVID-19 pandemic in the United States
J Jay et al, Nature Human Behavior, November 3, 2020 (Posted: Nov 06, 2020 8AM)

We used mobility data from a large, anonymized sample of smartphone users to assess the relationship between neighborhood income and physical distancing during the pandemic. We found a strong gradient between neighborhood income and physical distancing. Individuals in high-income neighborhoods increased their days at home substantially more than individuals in low-income neighborhoods did.

Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic
A Gollwitzer et al, Nature Human Behavior, November 2, 2020 (Posted: Nov 02, 2020 3PM)

Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics
R Gallotti et al, Nature Human Behavior, October 29, 2020 (Posted: Nov 02, 2020 3PM)

We analysed more than 100 million Twitter messages posted worldwide during the early stages of epidemic spread across countries and classified the reliability of circulating news. We developed an Infodemic Risk Index to capture the magnitude of exposure to unreliable news across countries. We found that measurable waves of potentially unreliable information preceded the rise of COVID-19, exposing entire countries to falsehoods that pose a serious threat to public health.

The SARS-CoV-2 effective reproduction rate has a high correlation with a contact index derived from large-scale individual location data using GPS-enabled mobile phones in Germany
S Ruediger et al, MEDRXIV, October 9, 2020 (Posted: Oct 11, 2020 9AM)

We derived the contact index, an index for the intensity of contact behavior from spatial proximity between individuals as proxy for physical interaction based on large-scale GPS mobile phone data of 1.15 to 1.4 million users A high correlation between the contact index and the effective reproduction number six days later could be observed in three different phases of the virus spread in Germany. Our model can potentially forecast the time evolution of the pandemic in Germany.

Airborne transmission of SARS-CoV-2
KA Prather et al, Science, October 5 2020 (Posted: Oct 06, 2020 7AM)

There is an urgent need to harmonize discussions about modes of virus transmission to ensure the most effective control strategies. To do so, we must clarify the terminology to distinguish between aerosols and droplets using a size threshold that can more effectively separate their aerodynamic behavior, ability to be inhaled, and efficacy of interventions.

Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
WE Allen et al, Nature Human Behavior, August 26, 2020 (Posted: Aug 26, 2020 8AM)

We developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behavior and demographics. Here, we report results from over 500,000 users in the United States. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals.

Research Questions for Aerosol Scientists Addressing COVID-19 and the Workplace
WG Lindsley et al, NIOSH Blog, August 2020 Brand (Posted: Aug 25, 2020 7AM)

Aerosol scientists bring a unique understanding of airborne particle behavior to infectious disease transmission studies. A recent commentary, “COVID-19 and the Workplace: Research Questions for the Aerosol Science Community,” presents some of the questions surrounding droplets and aerosols containing SARS-CoV-2 and provides suggestions for future research topics.

Mobility network modeling explains higher SARS-CoV-2 infection rates among disadvantaged groups and informs reopening strategies
SY Chang et al, MEDRXIV, August 14, 2020 (Posted: Aug 15, 2020 7AM)

We simulate the spread of SARS-CoV-2 from March 1 - May 2, 2020 among a population of 98 million people in 10 of the largest US metropolitan areas. We show that by integrating mobility networks, even a relatively simple epidemiological model can accurately capture the case trajectory despite dramatic changes in population behavior due to the virus.

Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19
A Aleta et al, Nature Human Behavior, August 5, 2020 (Posted: Aug 07, 2020 9AM)

We integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed model of transmission in Boston. We find that strict social distancing followed by testing, contact-tracing and quarantine could keep the disease within capacity of healthcare system while enabling the reopening of economic activities.

Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States
WE Allen et al, MEDRXIV, June 11, 2020 (Posted: Jun 13, 2020 8AM)

Applying principles of behaviour change to reduce SARS-CoV-2 transmission
R West et al, Nature Human Behavior, May 2020 (Posted: May 12, 2020 4PM)

There is an urgent need for direct evidence to inform development of behavioral interventions, but it is possible to make a start by applying behavioral science methods and models

Using genetics for social science
KP Harden et al, Nature Hum Behavior, May 11, 2020 (Posted: May 12, 2020 10AM)

We survey how developments in genetics are beginning to provide social scientists with a powerful new toolbox they can use to better understand environmental effects, and we illustrate this with several substantive examples. Furthermore, we examine how medical research can benefit from genetic insights into social-scientific outcomes and vice versa.

Genetic evidence for protective effects of smoking and drinking behavior on Parkinson's disease: A Mendelian Randomization study
CD Baleon et al, MEDRXIV, April 24, 2020 (Posted: Apr 24, 2020 8AM)

We use a two-sample Mendelian randomization (MR) experimental design to infer causal relationships between smoking (initiation, age of initiation, heaviness, and cessation) and alcohol (drinks per week) consumption as exposure variables and PD as the health outcome.

A cell phone data driven time use analysis of the COVID-19 epidemic
EP Fenichel et al, MEDRXIV, April 243 2020 (Posted: Apr 24, 2020 8AM)

We simulate epidemics in almost every county in the United States. The model suggests that Americans' behavioral shifts have reduced cases in 55%-86% of counties and for 71%-91% of the population, depending on modeling assumptions. Resuming pre-epidemic behavior would lead to a rapid rise in cases in most counties.

Assessing the risks of "infodemics" in response to COVID-19 epidemics
R Gallotti et al, MEDRXIV, April 11, 2020 (Posted: Apr 11, 2020 8AM)

We analyzed more than 100 millions Twitter messages posted worldwide in 64 languages during the epidemic emergency due to SARS-CoV-2 and classified the reliability of news diffused. We found that waves of unreliable and low-quality information anticipate the epidemic ones, exposing entire countries to irrational social behavior and serious threats for public health.

Understanding COVID-19 spreading through simulation modeling and scenarios comparison: preliminary results
MEDRXIV, April 1, 2020 (Posted: Apr 02, 2020 10AM)

The aim of this study is to provide an open model (using STELLA® from Iseesystems) that can be customized to any area/region and by any user, allowing them to evaluate the different behavior of the COVID-19 dynamics under different scenarios.

A Framework for Advancing Precision Medicine in Clinical Trials for Mental Disorders
EJ Lenze et al, JAMA Psychiatry, March 26, 2020 (Posted: Mar 29, 2020 8AM)

Getting the right treatment to the right patient is a frustrating goal in mental health: treatment is a trial-and-error endeavor, often yielding disappointing outcomes. Why? Traditional randomized clinical trials (RCTs) do not adequately capture the dynamic complexity of the brain and behavior during treatment.

COVID-19 and AI: A Virtual Conference
Stanford University, April 1, 2020 (Posted: Mar 16, 2020 8AM)

Topics to be addressed include: AI applications in diagnostics and treatment, epidemiological tracking and forecasting of the spread of the virus, information and disinformation, and the broader human impact of COVID-19 and pandemics in general on economies, culture, government, and human behavior.

What is the clinical value of mHealth for patients?
SP Rowland et al, NPJ Digital Medicine, January 13, 2020 (Posted: Jan 14, 2020 8AM)

The study categorizes apps according to their functionality (e.g. preventative behavior change, digital self-management of a specific condition, diagnostic) and discusses evidence for effectiveness from published systematic reviews and meta-analyses and the relevance to patient care.

Genetic factors, adherence to healthy lifestyle behavior, and risk of invasive breast cancer among women in the UK Biobank.
Arthur Rhonda S et al. Journal of the National Cancer Institute 2020 Jan (Posted: Jan 06, 2020 8AM)

Using regression models, we examined the association of a modified healthy lifestyle index (HLI) with risk of invasive breast cancer by genetic risk group among 146,326 women from the UK Biobank. The study shows that an overall healthy lifestyle may attenuate the impact of genetic factors on invasive breast cancer risk among women of European ancestry.

The Gene: An Intimate Story
NHGRI, 2019 Brand (Posted: Dec 22, 2019 6PM)

Science, social history and personal stories weave together a historical biography of the human genome while also exploring the stunning breakthroughs in understanding the impact genes play on heredity, disease and behavior.

Advancing the Promise of Digital Technology and Social Media to Promote Population Health.
Allegrante John P et al. Health education & behavior : the official publication of the Society for Public Health Education 2019 Dec 46(2_suppl) 5-8 (Posted: Nov 26, 2019 8AM)

We launched the 2018 Summit because of the ubiquity of digital technology and reach of social media, it had become apparent to us that the time was right to bring greater focus to the promise that digital technology and social media hold for improving the public's health.

Reaching Those at Highest Risk for Suicide: Development of a Model Using Machine Learning Methods for use With Native American Communities.
Haroz Emily E et al. Suicide & life-threatening behavior 2019 Nov (Posted: Nov 13, 2019 8AM)

Suicide prevention is a major priority in Native American communities. We used machine learning with community-based suicide surveillance data to better identify those most at risk. This study leverages data from the Celebrating Life program operated by the White Mountain Apache Tribe in Arizona.

Identification of risk variants and characterization of the polygenic architecture of disruptive behavior disorders in the context of ADHD
D Demontis et al, BioRXIV Genomics, October 2019 (Posted: Oct 22, 2019 9AM)

Here we report a large genome wide association meta-analysis of ADHD based on seven cohorts in total including 3,802 cases and 31,305 controls. Three genome-wide significant loci were identified on chromosomes 1, 7, and 11.

What health records data are required for accurate prediction of suicidal behavior?
Simon Gregory E et al. Journal of the American Medical Informatics Association : JAMIA 2019 Sep (Posted: Sep 25, 2019 9AM)

The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.Records from 7 large health systems identified 19 061 056 outpatient visits to mental health specialty or general medical providers between 2009 and 2015.

Social network interventions for health behaviours and outcomes: A systematic review and meta-analysis.
Hunter Ruth F et al. PLoS medicine 2019 Sep (9) e1002890 (Posted: Sep 05, 2019 8AM)

Evidence from this study suggests that social network interventions are associated with positive health behaviors and outcomes. ?Researchers and public health practitioners should consider how to use the social networks of their populations when delivering health behavior interventions in order to maximize effectiveness.

Warning signs: Can data from mobile phones anticipate a suicide attempt?
K Servick, Science, August 23, 2019 (Posted: Aug 23, 2019 1PM)

The goal is to combine machine learning with decades of evidence about what may trigger suicidal behavior to create an algorithm that detects spikes in risk. For adolescents, whose social and emotional lives are tightly bound to their phones, the approach could be especially powerful.

Human Behaviour Change Project
Human Behaviour Change Project, 2019 (Posted: Aug 20, 2019 9AM)

The Human Behaviour-Change Project (HBCP) is creating an online ‘Knowledge System’ that uses Artificial Intelligence, in particular Natural Language Processing and Machine Learning, to extract information from intervention evaluation reports to answer key questions about the evidence

BRIGHT Study Finds Genetic Testing Motivates Behavior Changes in Families at Risk for Melanoma
University of Utah, August 2019 (Posted: Aug 06, 2019 9AM)

The study showed genetic counseling about highly elevated melanoma risk, both with and without test reporting, led to sustained reductions in UVR exposure. The results provide evidence of unique benefit to participants who received genetic testing.

Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
JN Borger et al, NPJ Digital Medicine (Posted: Jul 29, 2019 1PM)

This study suggests that touchscreen interactions are widely integrated into modern sleeping habits—surrounding both sleep onset and waking-up periods—yielding a new approach to measuring sleep. Smartphone interactions can be leveraged to update the behavioral signatures of sleep with these peculiarities of modern digital behavior.

Comparison of adopted and non-adopted individuals reveals gene-environment interplay for education in the UK Biobank
R Cheesman et al, BioRXIV preprints, July 18, 2019 (Posted: Jul 20, 2019 4PM)

The study uses information from 6311 individuals in the UK Biobank who were adopted in childhood to compare genetic influence on education between adoptees and non-adopted individuals. The study provides another kind of evidence for the influence of parental behavior on offspring education.

What is the role of next generation sequencing in status epilepticus?
Guerrini Renzo et al. Epilepsy & behavior : E&B 2019 Jul (Posted: Jul 17, 2019 8AM)

Patterns of Communicating About Family Health History: Exploring Differences in Family Types, Age, and Sex.
Campbell-Salome Gemme et al. Health education & behavior : the official publication of the Society for Public Health Education 2019 Jun 1090198119853002 (Posted: Jun 26, 2019 9AM)

This study of more than 200 participants examined the direct and indirect effects of family communicative environments on whether individuals actively collected FHH information, as well as how age and sex differences complicate this relationship. Results show there was a direct effect between open family communicative environments and active collection, and found FHH communication openness was a positive partial mediator

By the numbers: ratings and utilization of behavioral health mobile applications
AD Carlo et al, NPJ Digital Medicine, June 17, 2019 (Posted: Jun 17, 2019 9AM)

Third-Party Genetic Interpretation Tools: A Mixed-Methods Study of Consumer Motivation and Behavior
SC Nelson et al, AJHG< June 13, 2019 (Posted: Jun 13, 2019 2PM)

Effect of Electronic Screening With Personalized Feedback on Adolescent Health Risk Behaviors in a Primary Care Setting A Randomized Clinical Trial
LP Richardson et al, JAMA Network Open (Posted: May 11, 2019 0PM)

Genetic and environmental sources of familial coaggregation of obsessive&#8722;compulsive disorder and suicidal behavior: a population-based birth cohort and family study
Sidorchuk A, et al. Molecular Psychiatry(2019) Apr 8 (Posted: Apr 09, 2019 8AM)

Effect of communicating phenotypic and genetic risk of coronary heart disease alongside web-based lifestyle advice: the INFORM Randomised Controlled Trial.
Silarova Barbora et al. Heart (British Cardiac Society) 2019 Mar (Posted: Apr 02, 2019 9AM)

Artificial intelligence can improve decision-making in infection management
TM Rawson et al, Nature Human Behavior, March 25, 2019 (Posted: Mar 26, 2019 9AM)

GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture
N Matoba et al, Nature Human Behavior, March 25, 2019 (Posted: Mar 26, 2019 9AM)

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Disclaimer: Articles listed in Hot Topics of the Day are selected by Public Health Genomics Branch to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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