Search

BackgroundThe COVID-19 pandemic has had a widespread impact on attendance in biomedical research and health care visits. ObjectiveThis study aimed to identify when and how American adults might feel comfortable about resuming in-person research and health care visits. MethodsCross-sectional questionnaire data were collected from 135 adults (age: median 48 years; women: n=113, 83.7%; White participants: n=92, 68.2%) who were engaged in health-related research. ResultsMore than half of the respondents (65/122, 53.3%) felt that the COVID-19 pandemic positively affected their desire to participate in research. Although 73.6% (95/129) of respondents also indicated a willingness to attend in-person health care visits while Centers for Disease Control and Prevention (CDC) guidelines are implemented, 85.8% (109/127) indicated a willingness to attend in-person, outdoor visits, and 92.2% (118/128) reported a willingness to attend drive-through visits (with CDC guidelines implemented during both visit types). Videoconferencing was the most preferred format for intervention visits; however, adults over the age of 65 years preferred this format less than younger adults (P=.001). ConclusionsResearchers and clinicians should continue to provide opportunities for continuing the conduction of remote-based interventions while enforcing CDC guidelines during in-person visits.

BackgroundElectronic health records (EHRs) hold great potential for longitudinal mother-baby studies, ranging from assessing study feasibility to facilitating patient recruitment to streamlining study visits and data collection. Existing studies on the perspectives of pregnant and breastfeeding women on EHR use have been limited to the use of EHRs to engage in health care rather than to participate in research. ObjectiveThe aim of this study is to explore the perspectives of pregnant and breastfeeding women on releasing their own and their infants’ EHR data for longitudinal research to identify factors affecting their willingness to participate in research. MethodsWe conducted semistructured interviews with pregnant or breastfeeding women from Alachua County, Florida. Participants were asked about their familiarity with EHRs and EHR patient portals, their comfort with releasing maternal and infant EHR data to researchers, the length of time of the data release, and whether individual research test results should be included in the EHR. The interviews were transcribed verbatim. Transcripts were organized and coded using the NVivo 12 software (QSR International), and coded data were thematically analyzed using constant comparison. ResultsParticipants included 29 pregnant or breastfeeding women aged between 22 and 39 years. More than half of the sample had at least an associate degree or higher. Nearly all participants (27/29, 93%) were familiar with EHRs and had experience accessing an EHR patient portal. Less than half of the participants (12/29, 41%) were willing to make EHR data available to researchers for the duration of a study or longer. Participants’ concerns about sharing EHRs for research purposes emerged in 3 thematic domains: privacy and confidentiality, transparency by the research team, and surrogate decision-making on behalf of infants. The potential release of sensitive or stigmatizing information, such as mental or sexual health history, was considered in the decisions to release EHRs. Some participants viewed the simultaneous use of their EHRs for both health care and research as potentially beneficial, whereas others expressed concerns about mixing their health care with research. ConclusionsThis exploratory study indicates that pregnant and breastfeeding women may be willing to release EHR data to researchers if researchers adequately address their concerns regarding the study design, communication, and data management. Pregnant and breastfeeding women should be included in EHR-based research as long as researchers are prepared to address their concerns.

BackgroundVitamin D deficiency is a well-documented public health issue with both genetic and environmental determinants. Populations living at far northern latitudes are vulnerable to vitamin D deficiency and its health sequelae, although consumption of traditional native dietary pattern rich in fish and marine mammals may buffer the effects of reduced sunlight exposure. To date, few studies have investigated the genetics of vitamin D metabolism in circumpolar populations or considered genediet interactions with fish and n-3 fatty acid intake.MethodsWe searched for genomic regions exhibiting linkage and association with circulating levels of vitamin D and parathyroid hormone (PTH) in 982 Yup'ik individuals from the Center for Alaska Native Health Research Study. We also investigated potential interactions between genetic variants and a biomarker of traditional dietary intake, the δ15N value.ResultsWe identified several novel regions linked with circulating vitamin D and PTH as well as replicated a previous linkage finding on 2p16.2 for vitamin D. Bioinformatic analysis revealed multiple candidate genes for both PTH and vitamin D, including CUBN, MGAT3, and NFKBIA. Targeted association analysis identified NEBL as a candidate gene for vitamin D and FNDC3B for PTH. We observed significant associations between a variant in MXD1 and vitamin D only when an interaction with the δ15N value was included. Finally, we integrated pathway level information to illustrate the biological validity of the proposed candidate genes.ConclusionWe provide evidence of linkage between several biologically plausible genomic regions and vitamin D metabolism in a circumpolar population. Additionally, these findings suggest that a traditional dietary pattern may modulate genetic effects on circulating vitamin D.

Scopen-3 polyunsaturated fatty acid (n-3 PUFA) intake is associated with protection from obesity; however, the mechanisms of protection remain poorly characterized. The stearoyl CoA desaturase (SCD), insulin-sensitive glucose transporter (SLC2A4), and sterol regulatory element binding protein (SREBF1) genes are transcriptionally regulated by n-3 PUFA intake and harbor polymorphisms associated with obesity. The present study investigated how consumption of n-3 PUFA modifies associations between SCD, SLC2A4, and SREBF1 polymorphisms and anthropometric variables and metabolic phenotypes.Materials and methodsAnthropometric variables and metabolic phenotypes were measured in a cross-sectional sample of Yup'ik individuals (n = 1135) and 33 polymorphisms were tested for main effects and interactions using linear models that account for familial correlations. n-3 PUFA intake was estimated using red blood cell nitrogen stable isotope ratios. SCD polymorphisms were associated with ApoA1 concentration and n-3 PUFA interactions with SCD polymorphisms were associated with reduced fasting cholesterol levels and waist-to-hip ratio. SLC2A4 polymorphisms were associated with hip circumference, high-density lipoprotein and ApoA1 concentrations. SREBF1 polymorphisms were associated with low-density lipoprotein and HOMA-IR and n-3 PUFA interactions were associated with reduced fasting insulin and HOMA-IR levels.ConclusionThe results suggest that an individual's genotype may interact with dietary n-3 PUFAs in ways that are associated with protection from obesity-related diseases in Yup'ik people.

ObjectiveTo identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people.Material and methodsWe measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks.ResultsWe observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004).ConclusionsThis study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people.

BackgroundGenome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D), mainly among individuals of European ancestry. In the present study, we examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (PUFA) intake, modify these associations.MethodsIn 1144 Yup'ik people, we examined 17 SNPs repeatedly identified in GWAS for individual and cumulative associations with T2D-related traits. Cumulative associations were evaluated using a genetic risk score (GRS) calculated by summing risk alleles. Associations were tested for interactions with sex, body mass index (BMI), and n-3 PUFA intake.ResultsThe rs7754840 SNP in CDKAL1 is significantly associated with HbA1c (P = 0.00091). The rs5015480 SNP near HHEX is significantly associated (in opposite direction to that in Europeans) with a combined fasting glucose (FG) and HbA1c measure (P = 0.00046) and with homeostatic model assessment of β-cell function (HOMA-B; P = 0.0014). The GRS is significantly associated with FG and combined FG and HbA1c only when the HHEX SNP is dropped from the GRS. Associations are not modified by BMI or n-3 PUFA intake.ConclusionOur results highlight the potential importance of CDKAL1 and HHEX in glucose homeostasis in this Alaska Native population with a low prevalence of T2D, and suggest that these loci should be examined in greater detail in this population.

BackgroundGenome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D), mainly among individuals of European ancestry. In the present study, we examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (PUFA) intake, modify these associations.MethodsIn 1144 Yup'ik people, we examined 17 SNPs repeatedly identified in GWAS for individual and cumulative associations with T2D-related traits. Cumulative associations were evaluated using a genetic risk score (GRS) calculated by summing risk alleles. Associations were tested for interactions with sex, body mass index (BMI), and n-3 PUFA intake.ResultsThe rs7754840 SNP in CDKAL1 is significantly associated with HbA1c (P = 0.00091). The rs5015480 SNP near HHEX is significantly associated (in opposite direction to that in Europeans) with a combined fasting glucose (FG) and HbA1c measure (P = 0.00046) and with homeostatic model assessment of β-cell function (HOMA-B; P = 0.0014). The GRS is significantly associated with FG and combined FG and HbA1c only when the HHEX SNP is dropped from the GRS. Associations are not modified by BMI or n-3 PUFA intake.ConclusionOur results highlight the potential importance of CDKAL1 and HHEX in glucose homeostasis in this Alaska Native population with a low prevalence of T2D, and suggest that these loci should be examined in greater detail in this population.

ObjectivesTo identify genomic regions associated with fasting plasma lipid profiles, insulin, glucose, and glycosylated hemoglobin in a Yup'ik study population, and to evaluate whether the observed associations between genetic factors and metabolic traits were modified by dietary intake of marine derived omega-3 polyunsaturated acids (n-3 PUFA).MethodsA genome-wide linkage scan was conducted among 982 participants of the Center for Alaska Native Health Research study. n-3 PUFA intake was estimated using the nitrogen stable isotope ratio (δ(15) N) of erythrocytes. All genotyped SNPs located within genomic regions with LOD scores > 2 were subsequently tested for individual SNP associations with metabolic traits using linear models that account for familial correlation as well as age, sex, community group, and n-3 PUFA intake. Separate linear models were fit to evaluate interactions between the genotype of interest and n-3 PUFA intake.ResultsWe identified several chromosomal regions linked to serum apolipoprotein A2, high density lipoprotein-, low density lipoprotein-, and total cholesterol, insulin, and glycosylated hemoglobin. Genetic variants found to be associated with total cholesterol mapped to a region containing previously validated lipid loci on chromosome 19, and additional novel peaks of biological interest were identified at 11q12.2-11q13.2. We did not observe any significant interactions between n-3 PUFA intake, genotypes, and metabolic traits.ConclusionsWe have completed a whole genome linkage scan for metabolic traits in Native Alaskans, confirming previously identified loci, and offering preliminary evidence of novel loci implicated in chronic disease pathogenesis in this population.

Variants of carnitine palmitoyltransferase 1A (CPT1A), a key hepatic lipid oxidation enzyme, may influence how fatty acid oxidation contributes to obesity and metabolic outcomes. CPT1A is regulated by diet, suggesting interactions between gene variants and diet may influence outcomes. The objective of this study was to test the association of CPT1A variants with body composition and lipids, mediated by consumption of polyunsaturated fatty acids (PUFA). Obesity phenotypes and fasting lipids were measured in a cross-sectional sample of Yup'ik Eskimo individuals (n = 1141) from the Center of Alaska Native Health Research (CANHR) study. Twenty-eight tagging CPT1A SNPs were evaluated with outcomes of interest in regression models accounting for family structure. Several CPT1A polymorphisms were associated with HDL-cholesterol and obesity phenotypes. The P479L (rs80356779) variant was associated with all obesity-related traits and fasting HDL-cholesterol. Interestingly, the association of P479L with HDL-cholesterol was still significant after correcting for body mass index (BMI), percentage body fat (PBF), or waist circumference (WC). Our findings are consistent with the hypothesis that the L479 allele of the CPT1A P479L variant confers a selective advantage that is both cardioprotective (through increased HDL-cholesterol) and associated with reduced adiposity.

Objective Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association—Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space. Process A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members. Conclusions Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of larger datasets is crucial to emulating the success AI is achieving in other domains. It is important that AI methods do not exacerbate existing socio-economic, racial, and ethnic disparities. Genomic data standards are critical to effectively scale such technologies across institutions. With so much uncertainty, complexity and novelty in genomics and medicine, and with an evolving regulatory environment, the current focus should be on using these technologies in an interface with clinicians that emphasizes the value each brings to clinical decision-making. [ABSTRACT FROM AUTHOR]

Background: Preeclampsia is a potentially fatal complication during pregnancy, characterized by high blood pressure and the presence of excessive proteins in the urine. Due to its complexity, the prediction of preeclampsia onset is often difficult and inaccurate. Objective: This study aimed to create quantitative models to predict the onset gestational age of preeclampsia using electronic health records. Methods: We retrospectively collected 1178 preeclamptic pregnancy records from the University of Michigan Health System as the discovery cohort, and 881 records from the University of Florida Health System as the validation cohort. We constructed 2 Cox-proportional hazards models: 1 baseline model using maternal and pregnancy characteristics, and the other full model with additional laboratory findings, vitals, and medications. We built the models using 80% of the discovery data, tested the remaining 20% of the discovery data, and validated with the University of Florida data. We further stratified the patients into high- and low-risk groups for preeclampsia onset risk assessment. Results: The baseline model reached Concordance indices of 0.64 and 0.61 in the 20% testing data and the validation data, respectively, while the full model increased these Concordance indices to 0.69 and 0.61, respectively. For preeclampsia diagnosed at 34 weeks, the baseline and full models had area under the curve (AUC) values of 0.65 and 0.70, and AUC values of 0.69 and 0.70 for preeclampsia diagnosed at 37 weeks, respectively. Both models contain 5 selective features, among which the number of fetuses in the pregnancy, hypertension, and parity are shared between the 2 models with similar hazard ratios and significant P values. In the full model, maximum diastolic blood pressure in early pregnancy was the predominant feature. Conclusions: Electronic health records data provide useful information to predict the gestational age of preeclampsia onset. Stratification of the cohorts using 5-predictor Cox-proportional hazards models provides clinicians with convenient tools to assess the onset time of preeclampsia in patients. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic created an unprecedented need for population-level clinical trials focused on the discovery of life-saving therapies and treatments. However, there is limited information on perception of research participation among perinatal populations, a population of particular interest during the pandemic. Methods: Eligible respondents were 18 years or older, were currently pregnant or had an infant (≤12 months old), and lived in Florida within 50 miles of sites participating in the OneFlorida Clinical Research Consortium. Respondents were recruited via Qualtrics panels between April and September 2020. Respondents completed survey items about barriers and facilitators to participation and answered sociodemographic questions. Results: Of 533 respondents, most were between 25 and 34 years of age (n = 259, 49%) and identified as White (n = 303, 47%) and non-Hispanic (n = 344, 65%). Facebook was the most popular social media platform among our respondents. The most common barriers to research participation included poor explanation of study goals, discomforts to the infant, and time commitment. Recruitment through healthcare providers was perceived as the best way to learn about clinical research studies. When considering research participation, "myself" had the greatest influence, followed by familial ties. Noninvasive biological samples were highly acceptable. Hispanics had higher positive perspectives on willingness to participate in a randomized study (p = 0.009). Education (p = 0.007) had significant effects on willingness to release personal health information. Conclusion: When recruiting women during the pregnancy and postpartum periods for perinatal studies, investigators should consider protocols that account for common barriers and preferred study information sources. Social media-based recruitment is worthy of adoption. [ABSTRACT FROM AUTHOR]