Research gaps and opportunities in precision nutrition: an NIH workshop report.
The American journal of clinical nutrition
Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On January 11-12, 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The Workshop proceeded in three parts: Part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer's disease, and cancer. Part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health. Part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches, and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.
View details for DOI 10.1093/ajcn/nqac237
View details for PubMedID 36055772
Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With COVID-19: A Systematic Review.
JAMA network open
2021; 4 (5): e2111417
Importance: Infection with COVID-19 has been associated with long-term symptoms, but the frequency, variety, and severity of these complications are not well understood. Many published commentaries have proposed plans for pandemic control that are primarily based on mortality rates among older individuals without considering long-term morbidity among individuals of all ages. Reliable estimates of such morbidity are important for patient care, prognosis, and development of public health policy.Objective: To conduct a systematic review of studies examining the frequency and variety of persistent symptoms after COVID-19 infection.Evidence Review: A search of PubMed and Web of Science was conducted to identify studies published from January 1, 2020, to March 11, 2021, that examined persistent symptoms after COVID-19 infection. Persistent symptoms were defined as those persisting for at least 60 days after diagnosis, symptom onset, or hospitalization or at least 30 days after recovery from the acute illness or hospital discharge. Search terms included COVID-19, SARS-CoV-2, coronavirus, 2019-nCoV, long-term, after recovery, long-haul, persistent, outcome, symptom, follow-up, and longitudinal. All English-language articles that presented primary data from cohort studies that reported the prevalence of persistent symptoms among individuals with SARS-CoV-2 infection and that had clearly defined and sufficient follow-up were included. Case reports, case series, and studies that described symptoms only at the time of infection and/or hospitalization were excluded. A structured framework was applied to appraise study quality.Findings: A total of 1974 records were identified; of those, 1247 article titles and abstracts were screened. After removal of duplicates and exclusions, 92 full-text articles were assessed for eligibility; 47 studies were deemed eligible, and 45 studies reporting 84 clinical signs or symptoms were included in the systematic review. Of 9751 total participants, 5266 (54.0%) were male; 30 of 45 studies reported mean or median ages younger than 60 years. Among 16 studies, most of which comprised participants who were previously hospitalized, the median proportion of individuals experiencing at least 1 persistent symptom was 72.5% (interquartile range [IQR], 55.0%-80.0%). Individual symptoms occurring most frequently included shortness of breath or dyspnea (26 studies; median frequency, 36.0%; IQR, 27.6%-50.0%), fatigue or exhaustion (25 studies; median frequency, 40.0%; IQR, 31.0%-57.0%), and sleep disorders or insomnia (8 studies; median 29.4%, IQR, 24.4%-33.0%). There were wide variations in the design and quality of the studies, which had implications for interpretation and often limited direct comparability and combinability. Major design differences included patient populations, definitions of time zero (ie, the beginning of the follow-up interval), follow-up lengths, and outcome definitions, including definitions of illness severity.Conclusions and Relevance: This systematic review found that COVID-19 symptoms commonly persisted beyond the acute phase of infection, with implications for health-associated functioning and quality of life. Current studies of symptom persistence are highly heterogeneous, and future studies need longer follow-up, improved quality, and more standardized designs to reliably quantify risks.
View details for DOI 10.1001/jamanetworkopen.2021.11417
View details for PubMedID 34037731
- 7th International Conference on Neurology and Epidemiology (ICNE), Virtual Conference, March 19-20, 2021. Neuroepidemiology 2021; 55 Suppl 1: 1-106
The timed 25-foot walk in a large cohort of multiple sclerosis patients.
Multiple sclerosis (Houndmills, Basingstoke, England)
The timed 25-foot walk (T25FW) is a key clinical outcome measure in multiple sclerosis patient management and clinical research.To evaluate T25FW performance and factors associated with its change in the Multiple Sclerosis Outcome Assessments Consortium (MSOAC) Placebo Database (n = 2465).We created confirmed disability progression (CDP) variables for T25FW and Expanded Disability Status Scale (EDSS) outcomes. We used intraclass correlation coefficients (ICCs) and Bland Altman plots to evaluate reliability. We evaluated T25FW changes and predictive validity using a mixed-effects model, survival analysis, and nested case-control analysis.The mean baseline score for the T25FW in this study population was 9.2 seconds, median = 6.1 (standard deviation = 11.0, interquartile range (IQR) = 4.8, 9.0). The T25FW measure demonstrated excellent test-retest reliability (ICC = 0.98). Walk times increased with age, disability, disease type, and disease duration; relapses were not associated with an increase. Patients with T25FW progression had a faster time to EDSS-CDP compared to those without (hazards ratio (HR): 2.6; confidence interval (CI): 2.2, 3.1). Changes in the T25FW were more likely to precede changes in EDSS.This research confirms the association of the T25FW with disability and provides some evidence of predictive validity. Our findings support the continued use of the T25FW in clinical practice and clinical trials.
View details for DOI 10.1177/13524585211017013
View details for PubMedID 34100297
Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.
OBJECTIVE: To develop and internally validate a multivariable predictive model for days with new-onset migraine headaches based on patient self-prediction and exposure to common trigger factors.BACKGROUND: Accurate real-time forecasting of one's daily risk of migraine attack could help episodic migraine patients to target preventive medications for susceptible time periods and help decrease the burden of disease. Little is known about the predictive utility of common migraine trigger factors.METHODS: We recruited adults with episodic migraine through online forums to participate in a 90-day prospective daily-diary cohort study conducted through a custom research application for iPhone. Every evening, participants answered questions about migraine occurrence and potential predictors including stress, sleep, caffeine and alcohol consumption, menstruation, and self-prediction. We developed and estimated multivariable multilevel logistic regression models for the risk of a new-onset migraine day vs a healthy day and internally validated the models using repeated cross-validation.RESULTS: We had 178 participants complete the study and qualify for the primary analysis which included 1870 migraine events. We found that a decrease in caffeine consumption, higher self-predicted probability of headache, a higher level of stress, and times within 2days of the onset of menstruation were positively associated with next-day migraine risk. The multivariable model predicted migraine risk only slightly better than chance (within-person C-statistic: 0.56, 95% CI: 0.54, 0.58).CONCLUSIONS: In this study, episodic migraine attacks were not predictable based on self-prediction or on self-reported exposure to common trigger factors. Improvements in accuracy and breadth of data collection are needed to build clinically useful migraine prediction models.
View details for DOI 10.1111/head.13960
View details for PubMedID 33022773
Sleep monitoring with the Apple Watch: comparison to a clinically validated actigraph
View details for DOI 10.12688/f1000research.19020.1