User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the world. Common comorbidities are central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome. Cardiovascular disease is the most common cause of death among people with NAFLD, and lifestyle changes can improve health outcomes.

OBJECTIVE

This study aims to explore the acceptability of a digital health program in terms of engagement, retention, and user satisfaction in addition to exploring changes in clinical outcomes, such as weight, cardiometabolic risk factors, and health-related quality of life.

METHODS

We conducted a prospective, open-label, single-arm, 12-week study including 38 individuals with either a BMI >30, metabolic syndrome, or type 2 diabetes mellitus and NAFLD screened by FibroScan. An NAFLD-specific digital health program focused on disease education, lowering carbohydrates in the diet, food logging, increasing activity level, reducing stress, and healthy lifestyle coaching was offered to participants. The coach provided weekly feedback on food logs and other in-app activities and opportunities for participants to ask questions. The coaching was active throughout the 12-week intervention period. The primary outcome was feasibility and acceptability of the 12-week program, assessed through patient engagement, retention, and satisfaction with the program. Secondary outcomes included changes in weight, liver fat, body composition, and other cardiometabolic clinical parameters at baseline and 12 weeks.

RESULTS

In total, 38 individuals were included in the study (median age 59.5, IQR 46.3-68.8 years; n=23, 61% female). Overall, 34 (89%) participants completed the program and 29 (76%) were active during the 12-week program period. The median satisfaction score was 6.3 (IQR 5.8-6.7) of 7. Mean weight loss was 3.5 (SD 3.7) kg (P<.001) or 3.2% (SD 3.4%), with a 2.2 (SD 2.7) kg reduction in fat mass (P<.001). Relative liver fat reduction was 19.4% (SD 23.9%). Systolic blood pressure was reduced by 6.0 (SD 13.5) mmHg (P=.009). The median reduction was 0.14 (IQR 0-0.47) mmol/L for triglyceride levels (P=.003), 3.2 (IQR 0.0-5.4) µU/ml for serum insulin (s-insulin) levels (P=.003), and 0.5 (IQR -0.7 to 3.8) mmol/mol for hemoglobin A1c (HbA1c) levels (P=.03). Participants who were highly engaged (ie, who used the app at least 5 days per week) had greater weight loss and liver fat reduction.

CONCLUSIONS

The 12-week-long digital health program was feasible for individuals with NAFLD, receiving high user engagement, retention, and satisfaction. Improved liver-specific and cardiometabolic health was observed, and more engaged participants showed greater improvements. This digital health program could provide a new tool to improve health outcomes in people with NAFLD.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05426382; https://clinicaltrials.gov/study/NCT05426382.

Abstract P519: Reduced Liver Fat and Improved Cardiometabolic Health in Individuals With Non Alcoholic Fatty Liver Disease After a 12 Week Digital Intervention - A Feasibility Study

Introduction: Cardiovascular disease is the most common cause of death among people with non-alcoholic fatty liver disease (NAFLD) and lifestyle changes can improve health outcomes. A NAFLD digital intervention was designed and here we report retention, engagement and satisfaction results in addition to the program's potential clinical impact on markers of liver- and cardiometabolic health.

Hypothesis: We assessed the hypothesis that a digital intervention is feasible for individuals with metabolic derangements and NAFLD to improve cardiometabolic health.

Methods: A prospective, open label, single arm, 12 week long study was conducted in Iceland.The intervention was delivered through the Sidekick app, with focus on disease education, low carbohydrate diet, increasing activity levels, reducing stress and healthy lifestyle coaching. Individuals with either BMI>30, metabolic syndrome or type 2 diabetes were screened for NAFLD with a FibroScan assessment. Other potential reasons for liver steatosis were excluded. Following recruitment and collection of demographic data, anthropometric and clinical measurements, MRI-PDFF for liver fat content, dual-energy X-ray absorptiometry for body composition and blood tests, were carried out at baseline and after 12 weeks. Primary outcomes were engagement and retention as measured in-app, and user satisfaction (mHealth App Usability Questionnaire); secondary outcomes were changes in weight, liver fat content and other cardiovascular risk factors.

Results: In total, 38 individuals were included in the study and 34 (89%) completed the program (defined as being active 9/12 weeks). The median age was 59.5 [IQR 46.0,69.0] years and 23 (60.5%) were females. The median number of active days was 81 [IQR 45.8, 84.0] and the median user satisfaction score was 6.3 out of 7. The mean weight loss was 3.5 kg (SD=3.7) (p<0.001) with 5.0% (SD=7.0) reduction in fat mass (p<0.001), the average relative liver fat reduction was 19.3% (SD=23.9) (p<0.001). Systolic blood pressure reduced by 6.0 mmHg on average (SD=13.5) (p=0.009), diastolic blood pressure by 1.2 mmHg (SD=7.7) (p=0.357), triglyceride levels by 0.3 mmol/L (SD=0.6) (p=0.003) and waist circumference by 4.1 cm (SD=5.2) (p<0.001). In addition, participants who were active in-app at least 5 days per week on average achieved 3.8 kg (SD=3.7) (p<0.001) more weight loss and 19.3% (SD=23.9) (p=0.011) higher reduction in absolute liver fat percentage, compared to those who used the app less.

Conclusion: This study suggests that a holistic digital intervention may improve liver-specific and cardiometabolic health in individuals with NAFLD, as indicated by the reduction in liver fat, systolic blood pressure and improvements in body composition. Together with the excellent program engagement, completion and satisfaction, this approach could provide a new tool to improve health outcomes in NAFLD.

Brain age prediction using deep learning uncovers associated sequence variants

Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual’s predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here, we present a new deep learning approach to predict brain age from a T1-weighted MRI. The method was trained on a dataset of healthy Icelanders and tested on two datasets, IXI and UK Biobank, utilizing transfer learning to improve accuracy on new sites. A genome-wide association study (GWAS) of PAD in the UK Biobank data (discovery set: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=12378$$\end{document}N=12378, replication set: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=4456$$\end{document}N=4456) yielded two sequence variants, rs1452628-T (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta =-0.08$$\end{document}β=−0.08, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P=1.15\times{10}^{-9}$$\end{document}P=1.15×10−9) and rs2435204-G (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta =0.102$$\end{document}β=0.102, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P=9.73\times 1{0}^{-12}$$\end{document}P=9.73×10−12). The former is near KCNK2 and correlates with reduced sulcal width, whereas the latter correlates with reduced white matter surface area and tags a well-known inversion at 17q21.31 (H2).

Machine learning algorithms can be trained to estimate age from brain structural MRI. Here, the authors introduce a new deep-learning-based age prediction approach, and then carry out a GWAS of the difference between predicted and chronological age, revealing two associated variants.

Rare and Common Variants Conferring Risk of Tooth Agenesis

We present association results from a large genome-wide association study of tooth agenesis (TA) as well as selective TA, including 1,944 subjects with congenitally missing teeth, excluding third molars, and 338,554 controls, all of European ancestry. We also tested the association of previously identified risk variants, for timing of tooth eruption and orofacial clefts, with TA. We report associations between TA and 9 novel risk variants. Five of these variants associate with selective TA, including a variant conferring risk of orofacial clefts. These results contribute to a deeper understanding of the genetic architecture of tooth development and disease. The few variants previously associated with TA were uncovered through candidate gene studies guided by mouse knockouts. Knowing the etiology and clinical features of TA is important for planning oral rehabilitation that often involves an interdisciplinary approach.

Predictors of carotid plaque progression over a 4-year follow-up in the Reykjavik REFINE-study

BACKGROUND AND AIMS

Carotid plaque is an arterial marker suggested as a surrogate end point for cardiovascular disease. The aim of this study was to examine the association of risk factors at visit 1 with plaque formation and progression of total plaque area (TPA) during follow-up.

METHODS

We examined 1894 participants (50-69 years of age) in the population-based REFINE (Risk Evaluation For INfarct Estimates)-Reykjavik study.

RESULTS

Among those with no plaque at baseline, plaque formation was associated with low density lipoprotein, sex, waist, former smoker and physical activity. Furthermore, both the Icelandic Heart Association (IHA) coronary heart disease (CHD) risk score and the atherosclerotic cardiovascular disease (ASCVD) risk score were highly associated with plaque formation in these individuals (p < 0.001) and a better cardiovascular health score was protective. In those with plaque present at baseline, metabolic syndrome was associated with increased risk, while older age and statin use were associated with reduced risk of new plaque formation. Statin use was the only factor associated with the relative TPA progression, where participants not on treatment had 5.7% (p=0.029) greater rate of progression compared with statin users.

CONCLUSIONS

A number of conventional risk factors at visit 1 were individually associated with plaque formation, also when combined into CHD and ASCVD risk scores, but not with the relative progression in TPA. Medical intervention with statins can reduce the relative progression rate of TPA in the general population with low grade of atherosclerosis, supporting statin use to slow progression of atherosclerosis.

15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia

Several copy number variants have been associated with neuropsychiatric disorders and these variants have been shown to also influence cognitive abilities in carriers unaffected by psychiatric disorders. Previously, we associated the 15q11.2(BP1-BP2) deletion with specific learning disabilities and a larger corpus callosum. Here we investigate, in a much larger sample, the effect of the 15q11.2(BP1-BP2) deletion on cognitive, structural and functional correlates of dyslexia and dyscalculia. We report that the deletion confers greatest risk of the combined phenotype of dyslexia and dyscalculia. We also show that the deletion associates with a smaller left fusiform gyrus. Moreover, tailored functional magnetic resonance imaging experiments using phonological lexical decision and multiplication verification tasks demonstrate altered activation in the left fusiform and the left angular gyri in carriers. Thus, by using convergent evidence from neuropsychological testing, and structural and functional neuroimaging, we show that the 15q11.2(BP1-BP2) deletion affects cognitive, structural and functional correlates of both dyslexia and dyscalculia.

Prevalence and determinants of carotid plaque in the cross-sectional REFINE-Reykjavik study

OBJECTIVE

Carotid plaque and intima-media thickness are non-invasive arterial markers that are used as surrogate end points for cardiovascular disease. The aim was to assess the prevalence and severity of carotid plaque, and examine its determinant risk factors and their association to the common carotid artery intima-media thickness (CCA-IMT) in a general population.

METHODS

We examined 6524 participants aged 25-69 years in the population-based REFINE (Risk Evaluation For INfarct Estimates)-Reykjavik study. Plaques at the bifurcation and internal carotid arteries were evaluated. Mean CCA-IMT was measured in the near and far walls of the common carotid arteries.

RESULTS

The prevalence of minimal, moderate and severe plaque was 35.0%, 8.9% and 1.1%, respectively, and the mean CCA-IMT was 0.73 (SD 0.14) mm. Age, sex, smoking and type 2 diabetes mellitus (T2DM) were the strongest risk factors associated with plaque, followed by systolic blood pressure, total cholesterol, body mass index and family history of myocardial infarct. Low educational level was also strongly and independently associated with plaque. CCA-IMT shared the same risk factors except for a non-significant association with T2DM and family history of myocardial infarction (MI). Participants with T2DM had greater plaque prevalence, 2-fold higher in those <50 years and 17-30% greater in age groups 50-54 to 60-64, and more significant plaques (moderate or severe) were the difference in prevalence was 24% in age group 50-54 and ≥60% in older age groups, compared with non-T2DM.

CONCLUSIONS

Carotid plaque and CCA-IMT have mostly common determinants. However, T2DM and family history of MI were associated with plaque but not with CCA-IMT. Greater prevalence and more severe plaques in individuals with T2DM raise the concern that with increasing prevalence of T2DM we may expect an increase in atherosclerosis and its consequences.

A rare missense mutation in CHRNA4 associates with smoking behavior and its consequences

Using Icelandic whole-genome sequence data and an imputation approach we searched for rare sequence variants in CHRNA4 and tested them for association with nicotine dependence. We show that carriers of a rare missense variant (allele frequency=0.24%) within CHRNA4, encoding an R336C substitution, have greater risk of nicotine addiction than non-carriers as assessed by the Fagerstrom Test for Nicotine Dependence (P=1.2 × 10(-4)). The variant also confers risk of several serious smoking-related diseases previously shown to be associated with the D398N substitution in CHRNA5. We observed odds ratios (ORs) of 1.7-2.3 for lung cancer (LC; P=4.0 × 10(-4)), chronic obstructive pulmonary disease (COPD; P=9.3 × 10(-4)), peripheral artery disease (PAD; P=0.090) and abdominal aortic aneurysms (AAAs; P=0.12), and the variant associates strongly with the early-onset forms of LC (OR=4.49, P=2.2 × 10(-4)), COPD (OR=3.22, P=2.9 × 10(-4)), PAD (OR=3.47, P=9.2 × 10(-3)) and AAA (OR=6.44, P=6.3 × 10(-3)). Joint analysis of the four smoking-related diseases reveals significant association (P=6.8 × 10(-5)), particularly for early-onset cases (P=2.1 × 10(-7)). Our results are in agreement with functional studies showing that the human α4β2 isoform of the channel containing R336C has less sensitivity for its agonists than the wild-type form following nicotine incubation.

HeartCare: an Internet-based information and support system for patient home recovery after coronary artery bypass graft (CABG) surgery

HeartCare is an Internet-based information and support service for patients recovering at home from coronary artery bypass graft (CABG) surgery. The system is designed to meet the nursing challenges in health information to support needs of CABG patients. HeartCare (a) provides information and support, tailored to patients' individual and changing recovery needs during CABG recovery, (b) makes recovery information more accessible for timely use by patients, and (c) extends the scope of nursing services to CABG patients from hospital through home. An ongoing randomized controlled study is underway to evaluate the clinical outcomes of patients' use of the HeartCare system and to examine its acceptance as a usable resource for postCABG patients who have limited previous computer experience.

Online social support for individuals concerned with heart disease: observing gender differences

Using a theoretical framework of social support, and content analysis, the content and pattern of support in messages posted in a 4-week period on a commercial health network for individuals concerned with heart disease were observed and described. Special consideration was given to identifying gender differences.