Additional file 1.pdf

The supplementary figures of "Integrative methylation score to identify epigenetic modifications associated with lipid changes resulting from fenofibrate treatment in families"

Data_Sheet_1_Prediction of progression from mild cognitive impairment to Alzheimer's disease with longitudinal and multimodal data.docx

IntroductionAccurate prediction of the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) within a certain time frame is crucial for appropriate therapeutic interventions. However, it is challenging to capture the dynamic changes in cognitive and functional abilities over time, resulting in limited predictive performance. Our study aimed to investigate whether incorporating longitudinal multimodal data with advanced analytical methods could improve the capability to predict the risk of progressing to AD.MethodsThis study included participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a large-scale multi-center longitudinal study. Three data modalities, including demographic variables, neuropsychological tests, and neuroimaging measures were considered. A Long Short-Term Memory (LSTM) model using data collected at five-time points (baseline, 6, 12, 18, and 24-month) was developed to predict the risk of progression from MCI to AD within 2 years from the index exam (the exam at 24-month). In contrast, a random forest model was developed to predict the risk of progression just based on the data collected at the index exam.ResultsThe study included 347 participants with MCI at 24-month (age: mean 75, SD 7 years; 39.8% women) from ADNI, of whom 77 converted to AD over a 2-year follow-up period. The longitudinal LSTM model showed superior prediction performance of MCI-to-AD progression (AUC 0.93 ± 0.06) compared to the random forest model (AUC 0.90 ± 0.09). A similar pattern was also observed across different age groups.DiscussionOur study suggests that the incorporation of longitudinal data can provide better predictive performance for 2-year MCI-to-AD progression risk than relying solely on cross-sectional data. Therefore, repeated or multiple times routine health surveillance of MCI patients are essential in the early detection and intervention of AD.</p

Additional file 1: Table S1. of Whole blood gene expression and white matter Hyperintensities

Association of top genes with WMH after excluding samples with stroke, dementia or vascular diseases. Table S2. Association of top genes with WMH after additionally adjusted for the RNA integrity number (RIN). Table S3. Separated analysis for participants from the Offspring cohort and the Third Generation cohort. Table S4. Association of top genes within cognitive performance. Figure S1. Correlation between the statistics of WMH associations derived from the imputed cell counts or the measured cell counts using those samples who have measured cell counts. X-axis represents the statistics derived from measured cell counts, while y-axis represents the statistics derived from the imputed cell counts. Strong correlation was observed (R2 = 0.984), suggesting only marginal effect of imputed cell counts. (PDF 187 kb

Most significant transcripts associated with prevalent AF (FDR<0.05).

<p>*SE: Standard error; FDR: false discovery rate <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096794#pone.0096794-Benjamini1" target="_blank">[32]</a>.</p

Most significant canonical pathways enriched with genes in the AF subnetwork (FDR<0.005).

+<p>Ratio is the number of genes within AF subnetwork comparing to the total number of genes in the pathway.</p

AF subnetwork derived from protein-protein interaction.

<p>Each node represents one gene, wheras each edge represents the interaction between two genes. The nodes were colored to represent their association with AF: red color represents strong association, and white color represents no association. The node size is proportional to the number of edges that the node connects to.</p

Clinical characteristics of the sample.

<p>Clinical characteristics of the sample.</p

Most significant transcripts associated with prevalent AF (FDR<0.05).

<p>*SE: Standard error; FDR: false discovery rate <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096794#pone.0096794-Benjamini1" target="_blank">[32]</a>.</p

Table_1_Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates.DOCX

IntroductionAlthough the growth of digital tools for cognitive health assessment, there’s a lack of known reference values and clinical implications for these digital methods. This study aims to establish reference values for digital neuropsychological measures obtained through the smartphone-based cognitive assessment application, Defense Automated Neurocognitive Assessment (DANA), and to identify clinical risk factors associated with these measures.MethodsThe sample included 932 cognitively intact participants from the Framingham Heart Study, who completed at least one DANA task. Participants were stratified into subgroups based on sex and three age groups. Reference values were established for digital cognitive assessments within each age group, divided by sex, at the 2.5th, 25th, 50th, 75th, and 97.5th percentile thresholds. To validate these values, 57 cognitively intact participants from Boston University Alzheimer’s Disease Research Center were included. Associations between 19 clinical risk factors and these digital neuropsychological measures were examined by a backward elimination strategy.ResultsAge- and sex-specific reference values were generated for three DANA tasks. Participants below 60 had median response times for the Go-No-Go task of 796 ms (men) and 823 ms (women), with age-related increases in both sexes. Validation cohort results mostly aligned with these references. Different tasks showed unique clinical correlations. For instance, response time in the Code Substitution task correlated positively with total cholesterol and diabetes, but negatively with high-density lipoprotein and low-density lipoprotein cholesterol levels, and triglycerides.DiscussionThis study established and validated reference values for digital neuropsychological measures of DANA in cognitively intact white participants, potentially improving their use in future clinical studies and practice.</p

Manhattan plot of common variant associations with atrial fibrillation.

<p>Manhattan plot of common variant associations with atrial fibrillation.</p