Independently, physical activity (PA), sedentary behavior (SB), and sleep are related to the development and progression of chronic diseases. Less is known about how rest-activity behaviors cluster within individuals and how rest-activity behavior profiles relate to health. In this study we aimed to investigate if adult women cluster into profiles based on how they accumulate rest-activity behavior , and if participant characteristics and health outcomes differ by profile membership.A convenience sample of 372 women (mean age 55.38 + 10.16) were recruited from four US cities. Participants wore ActiGraph GT3X+ accelerometers on the hip and wrist for a week. Total daily minutes in moderate-to-vigorous PA (MVPA) and percentage of wear-time spent in SB was estimated from the hip device. Total sleep time (hours/minutes) and sleep efficiency (% of in bed time asleep) were estimated from the wrist device. Latent profile analysis (LPA) was performed to identify clusters of participants based on accumulation of the four rest-activity variables. Adjusted ANOVAs were conducted to explore differences in demographic characteristics and health outcomes across profiles.Rest-activity variables clustered to form five behavior profiles: Moderately Active Poor Sleepers (7%), Highly Actives (9%), Inactives (41%), Moderately Actives (28%), and Actives (15%). The Moderately Active Poor Sleepers (profile 1) had the lowest proportion of whites  and college graduates . Health outcomes did not vary significantly across all rest-activity profiles.In this sample, women clustered within daily rest-activity behavior profiles. Identifying 24-hour behavior profiles can inform intervention population targets and innovative behavioral goals of multiple health behavior interventions. Low levels of physical activity (PA) and high levels of sedentary behavior (SB) have been identified as major modifiable risk factors for chronic diseases such as diabetes, obesity, and cardiovascular disease –3. SimilPrevious research has primarily examined these rest-activity behaviors  individually and their associations with relevant health outcomes . In reality, these rest-activity behaviors do not occur in isolation, and time spent in PA, SB, and sleep aggregates to make up the finite 24-hour day. Variable-centered analyses do not allow for us to develop an understanding of how rest-activity behaviors aggregate within individuals to impact their health. Further, evidence indicates that daily rest-activity activity behaviors are interrelated, suggesting that an individual’s engagement in one activity is associated with engagement in another. In an NHANES sample of 2,989 adults, lower levels of daily PA was associated with higher self-reported sleep disturbance scores . Little The clustering analysis  approach has been widely used to explore daily activity behavior profiles in youth and adolescent samples and their associations to health outcomes –12. In aThis study aimed to leverage a free-living cohort of middle aged to older women across the US, including working adults, nurses, and breast cancer survivors. Using objectively measured rest-activity behavior data we will apply clustering analyses to explore: 1) whether women cluster into rest-activity behavior profiles based on how they accumulate total sleep time, sleep efficiency, PA, and SB, and if 2) if demographic characteristics and health outcomes vary according to rest-activity behavior profiles.2, have the ability to ambulate unassisted, not be pregnant or breast-feeding, and be willing to wear monitoring devices for 7 days. Site-specific eligibility criteria included: current full or part-time employment (WUSTL) and a previous breast cancer diagnosis (UPenn). The Harvard sample was selected to evenly represent all Census regions of the US (African American were oversampled).Our convenience sample included 372 adult women participating in studies across four university sites in the US , Washington University in St. Louis (WUSTL), Harvard University (Harvard), and University of Pennsylvania (UPenn)) involved in the NCI-funded Transdisciplinary Research in Energetics and Cancer (TREC) initiative . Across Data collection was conducted remotely for the Penn, Harvard, and WUSTL sites and in person for the UCSD site. In the remote data collection scenarios, accelerometers were mailed to 87% of participants with instructions, a link to an instructional video, and a paper survey. Paper surveys were completed by participants and returned via mail. For the remaining participants at UCSD, accelerometers were received and returned in person. Study protocols specific to the collection of accelerometer data and survey completion were identical across all sites and all data used in these analyses were centrally pooled and uniformly processed at UCSD . The accModerate-to-vigorous physical activity (MVPA) and sedentary behavior were measured objectively using a hip-worn Actigraph GT3X+ , a lightweight triaxial accelerometer. The ActiGraph device has been validated and calibrated for physical activity and sedentary behavior measurement in the field and in controlled conditions . The accSleep was measured using a wrist-worn Actigraph GT3X+ accelerometer, in conjunction with a self-reported sleep log. Participants were instructed to wear the wrist accelerometer for 24 hours per day during the monitoring period, and to record their in-bed and out-of-bed times for each sleep period in the sleep log. Sleep was scored using the log-reported in bed and out of bed time to define the major sleep period, adhering to SBSM actigraphy use guidelines . A valid2) was calculated using self-reported height and weight. Self-rated health was rated on a 1 (“Poor”) to 5 (“Excellent”) scale. Health conditions were assessed via the question “Do you currently have, or has a physician told you that you have any of the following health conditions?” A count of health conditions was created from a list of 16 possibilities, and participants were grouped categorically as: 0, 1, 2, or ≥ 3. Physical functioning was measured using a subset of the Short Form-36 Health Survey [All participants completed a study survey when they received their measurement devices. The survey assessed age (years), race/ethnicity, marital status, education, self-rated health, and disease diagnoses. Race/ethnicity was dichotomized into white or racial/ethnicity minority . Marital status was dichotomized into married (or living with a partner) or non-married . Education was dichotomized into having a college degree (bachelor or graduate degree) or not . BMI  were assessed at the daily level. Two participant-level variables were created for each behavior by taking the mean and standard deviation (SD) of each daily-level variable across days. Bivariate Pearson’s correlations were used to investigate associations among the four daily mean variables.Latent profile analyses were conducted on the four participant-level daily mean variables to derive mutually exclusive classes (clusters) that maximize between-group variance while minimizing within-group variance. The model uses the distributional assumptions to find classes. This approach was chosen over a regression model approach, with the intention of going beyond examining if two of the four rest-activity behavior variables are related to one another to examine if multiple rest-activity behaviors cluster together within individuals. This approach has the potential to generate participant behavior profiles that will allow for the further exploration of differences in demographics and health outcomes across behavior profile groups.Model fits were compared to derive the number of profiles that best fit the data , using tOnce the continuous rest-activity behavior profiles were identified, we investigated whether we could identify differences in social demographic characteristics across the profile groups. Analysis of variance (ANOVA) with Bonferroni post-hoc tests were used to compare differences in age, race/ethnicity, and education across the latent profiles (separate models). To account for the differences in sample populations, these models adjusted for study site and additional demographic characteristics (i.e. the model comparing age adjusted for race/ethnicity and education). Additional ANOVA models were then used to assess differences in participant health characteristics previously associated in the literature with daily rest-activity variables  across behavior profiles. Health conditions were grouped categorically as: 0, 1, 2, or ≥3. Models adjusted for covariates selected a priori including: age, race/ethnicity, education, and site.MPlus 6.12 was used for all of the statistical analyses.Of the 402 people recruited to the study, 368 (92%) returned both wrist and hip accelerometers with valid wear, and an additional 4 people returned accelerometers with valid data after requesting a re-wear, resulting in a final analytic sample of 372 participants. The all-female study sample had an average age of 55.38 (SD = 10.16) years . Particir = -0.31, p < 0.01). Of note, nightly sleep time and sleep efficiency were only moderately correlated . Neither MVPA nor SB were significantly correlated with either sleep behavior variable.Univariate Pearson’s correlations were run to examine possible correlations between the rest-activity behavior variables. As expected, percent sedentary time (SB) and daily MVPA showed a moderate inverse correlation . Women in this group were close to meeting sleep recommendations but spent more time in SB (66% time) and were the least physically active (7 minutes/day of MVPA) compared to women in the other groups.Overall, sleep characteristics did not vary greatly across all profiles. Profile 1 (Moderately Active Poor Sleepers) was the only group to have significantly poorer sleep characteristics than the other four profiles. Additionally, the comparison of SDs of the sleep variables indicates more night-to-night variability in the sleep of women in Profile 1 compared to the other behavior profiles. Women in Profile 2 (Highly Actives) did not meet sleep duration guidelines, but had moderately high sleep efficiency (87%) and overall sleep characteristics did not differ significantly from profiles 3.1, 3.2, or 3.3.Only 2 profiles (Profile 2 and 3.3), comprising 24% of women, met daily MVPA recommendations. Mean daily MVPA was as high as 65 minutes/day in the Highly Actives and as low as 6.77 minutes/day for the Inactives. Sedentary time did not vary across behavior profiles to the extent that MVPA did, as there was only a 10% difference in sedentary time between the profile with the most (profile 3.1: 66% sedentary) and least SB (profile 2: 56% sedentary).In our additional exploratory analyses demographic characteristics did not differ significantly across the behavior profile groups. There were no significant differences in profile membership based on study site (data not shown). Age was largely comparable across rest-activity behavior profiles, with one significant difference (p = .001) between the Inactives  and the Actives . Race-ethnicity and education did not vary across all of the profiles, however the Inactives had a significantly lower proportion of whites , and a lower proportion of college graduates  than all of the other behavior profiles. Marital status did not differ significantly across profiles.Additionally, health outcomes did not vary significantly across all rest-activity profiles. Significant differences in BMI were only observed between the Inactives, who reported the highest BMI , and the Moderately Actives , but not the other profiles. Physical functioning was also largely similar among behavior profiles, with significant differences observed between the Moderately Active Poor Sleepers, who reported the lowest physical functioning scores , and the Moderately Actives who reported the highest physical functioning scores . Self-rated health and reported number of health conditions did not differ significantly across behavior profiles, however means trended in the expected directions . Additionally, the women in the Moderately Active Poor Sleepers group were more likely to report working a regular night shift (12% vs. 0–2%) and having a sleep disorder (14% vs. 7–9%) than members of the other behavior profiles, although these differences were not statistically significant (data not presented in table).This was one of the first studies to use objectively measured PA, SB, and sleep to explore the clustering of 24-hour rest-activity behaviors in adult women. Five different rest-activity behavior profiles emerged from our analysis. Demographic characteristics and health outcomes did not vary significantly across behavior profiles. However, we found the behavior profile with the least MVPA and highest percent time in SB had the highest mean BMI, and the behavior profile with the shortest nightly sleep time and lowest sleep efficiency had the poorest physical functioning. The results of this clustering analysis support future studies further exploring the interrelationship of 24-hour rest-activity behaviors among adults.In our sample of adult women, MVPA was the largest discriminator across the resulting rest-activity behavior profiles. Overall, only 24% of women in our sample achieved mean daily minutes of MVPA that met the 2018 PA guidelines for adults, which is similar to recent population estimates of women meeting PA guidelines in the United States . AdditioIn this study, sleep characteristics did not vary significantly across the resulting 24-hour rest-activity behavior profiles. Overall, the entire sample of women had average nightly sleep times that were just under meeting the national recommendations of 7–9 hours per night . Only onConsistent with previous research, in our study the behavior profile with the lowest minutes of daily MVPA and highest SB had the highest BMI . The behThis study has several limitations. While the study data were collected daily allowing for possible longitudinal assessment, this study was cross-sectional and averages of daily activities were assessed to answer the research questions. Due to the cross-sectional design examining causal relationships between profile membership and health conditions was not possible. Actigraphy was used to measure PA (gold standard), however this approach is limited in its ability to capture certain PA modalities, such as swimming and cycling. Accelerometers were also used to measure sleep rather than the gold standard polysomnography. While our analysis included a unique sample of women varied in age, health status, and occupation, all participants were adult women, which limits the generalizability of these findings to US adult men. Health variables were all self-reported and were limited in scope and severity. While the sample size of 372 was large enough to discern five distinct profiles, a larger sample size would have greater statistical power to discern differences between these groups. Lastly, we acknowledge that some of the model fit statistics may support that a 2-class solution better represented the participants in the second LPA, however we believe that substantive interpretation lends support for a 3-class solution to this model.Few studies have investigated how women cluster in rest-activity behavior profiles based on their accumulation of activity throughout the 24-hour day. This study is one of the first to explore 24-hour behavior patterns in women using objective measures of 24-hour daily activity behavior. This study demonstrates that women cluster into distinct behavior profile groups based on their daily MVPA, SB, and sleep characteristics. Prior studies have relied upon self-reported measures of these behaviors and have typically examined behaviors individually, ignoring the possible interrelationships of daily activity behaviors. This analysis supports the use of future longitudinal studies to further untangle the interrelationships of these behaviors and understand how behavior profiles may be associated with health outcomes over time. Additionally, more research is needed to determine whether these behavior profiles generalize to other population subgroups  and racial-ethnically diverse samples. While more research is needed, this study demonstrates the importance of considering the clustering of rest-activity behaviors in intervention design and population targeting. This study provides promising evidence to support the further exploration of multiple behavior change interventions and identifying populations most in need of lifestyle intervention, including the populations with the lowest MVPA and poorest sleep characteristics –38.


Speech (spoken sentences), Hum (hummed melodies), and Song (sung sentences); the sentences used in Speech and Song categories were the same, as well as the melodies used in the two musical categories. Each category had a scrambled counterpart which allowed us to render speech and melody unintelligible, while preserving global amplitude and frequency characteristics. Finally, we included a group of musicians to evaluate the influence of musical expertise. Similar global patterns of cortical activity were related to all sound categories compared to baseline, but important differences were evident. Regions more sensitive to musical sounds were located bilaterally in the anterior and posterior superior temporal gyrus , the right supplementary and premotor areas, and the inferior frontal gyrus. However, only temporal areas and supplementary motor cortex remained music-selective after subtracting brain activity related to the scrambled stimuli. Speech-selective regions mainly affected by intelligibility of the stimuli were observed on the left pars opecularis and the anterior portion of the medial temporal gyrus. We did not find differences between musicians and non-musicians Our results confirmed music-selective cortical regions in associative cortices, independent of previous musical training.A fundamental question regarding music processing is its degree of independence from speech processing, in terms of their underlying neuroanatomy and influence of cognitive traits and abilities. Although a straight answer to that question is still lacking, a large number of studies have described where in the brain and in which contexts  this independence is, or is not, observed. We examined the independence between music and speech processing using functional magnetic resonance imagining and a stimulation paradigm with different human vocal sounds produced by the same voice. The stimuli were grouped as  Despite continuous debate regarding the level of functional, anatomical and cognitive independence between speech and music processing –5, it isThe immediate question when comparing music and speech refers to human vocalizations, given that they represent the most common sound in our environment, and the most ancient expression of music and language –29. In aPrevious findings have shown that regardless of musical stimuli being human vocalizations (such as a syllabic hum or song) there are certain differences in brain activity when compared to that elicited by speech, particularly a right hemisphere lateralization for music processing which could be modulated depending on the content of lyrics or tasks involved ,32,33,39Speech, Song and Hum) affecting the intelligibility of the vocal sound but preserving the amplitude and spectral features. In the same way, we controlled for semantic content and included different sentences that were sung and spoken by a professional singer. Melodic content was the same for the hummed and sung stimuli.Given this, our goal was to evaluate at which point in the hierarchy of the auditory pathway these two acoustic signals show divergent processing, and if these differences in brain activation are maintained after altering some of the basic acoustic properties, which are supposed to involve primary areas of the auditory cortex according to the hierarchical functional organization –42. To aSong and Speech) but would differ with respect to the music category without verbal content (Hum). Based on previous results and numerous studies showing brain differences  in musicians as a result of training  > [Song>Song-S]) showed the caudate nucleus, bilaterally.This analysis compared the brain activation associated to We evaluated whether musical training differentially modulated brain activity while listening to our experimental paradigm. All the contrasts described in Analyses 2–4 were tested for group differences, with none being statistically significant.planum polare, planum temporale and Heschl’s gyrus. * p < 0.0028; # p < 0.05). We found statistically significant differences between Song and Speech in the left and right planum polare, and also between Song and Hum; the lowest levels of activation within the planum polare were observed in the Speech category. BOLD responses in Heschl's gyrus (A1) were lower in response to Hum as compared to those elicited by Song or Speech, bilaterally; there were no differences in A1 activation between the last two categories. In parallel with this observation, acoustic feature analyses showed that Hum differs substantially from Song/Speech in several aspects, such as zero-cross, and spectral spread, brightness, centroid, kurtosis and flatness , melodic, and semantic content .In this study we aimed to further explore brain regions modulated for music as compared to speech. In Particular, we investigated whether this selectivity changed when we combined the two domains , by comparing the Song > Song-S revealed bilateral activation of the planum polare and temporale, left PMC and SMA. This result suggests these areas are not exclusively modulated by low-level acoustic parameters, but also by the temporal structure affecting the semantic, syntactic and melodic-contour, as has been reported in other musical studies [To identify brain regions sensitive to musical sounds at different processing levels, we first compared each natural vocal category against their scrambled versions. We observed that while all acoustic categories recruited different regions of the STG when compared them to their scrambled version, only the musical categories also revealed activation maps covering the SMA and PMC. This result confirms what has been previously described in speech processing showing that music is also hierarchically encoded involving brain regions beyond Heschl’s gyrus ,20,51,52 studies ,55,56.Song-S > Song) revealed consistent higher BOLD modulations in Heschl’s gyrus. The increased activity in response to scrambled acoustic stimuli, independently of acoustic category, is indicative of converging processing of music and speech processing at this level. The primary auditory cortex presents a tonotopical organization sensitive to frequency tuning and spectro-temporal modulations [The opposite contrasts comparing the scrambled versions  > (Speech>Speech-S)  > (Speech>Speech-S)  was not more responsive to Hum as it was to Speech. Thus, the planum polare showed higher levels of activation in both musical conditions, particularly when intelligibility was not affected. However, stronger bilateral activation was observed when vocal music included lyrics , likely reflecting the simultaneous processing of speech and music present in Song. This finding was corroborated with an unbiased ROI analysis , suggesting it has a shared functional identity during vocal music and speech processing, specially when they are combined (Song). On the other hand, the left planum temporale was equally modulated by Speech and Song categories, confirming its preference for stimuli with verbal content , possibly associated with representations of lexical or semantic structures [Once we had identified the brain regions that are sensitive to the temporal structure of acoustic stimuli, we searched for the functional independence between music and speech processing. The contrast (peech-S)  showed tpeech-S) , highliganalysis . In linepatterns ,63. The ent task ,24 and dent task ,33,64. Sructures ,65,66.Our results showed music-sensitivity in cortical motor regions such as the SMA and the PMC, which have been related to beat and rhythm perception –72. Partplanum temporale, STS, IFG, post-central gyrus and the ventral division of M1) [Speech elicited larger activity than Hum in the entire left MTG  ,75, whicleft MTG , only thhan Song , suggestplanum polare and the right planum temporale, when listening to different types of instrumental music stimuli in comparison to speech [In a previous study, we found differences between musicians and non-musicians involving greater bilateral activity of the o speech . In our o speech ,50. The Speech and Song conditions, for example. Temporal resolution is also limited in all fMRI studies, and there is a wealth of information from rapid temporal fluctuations present in music and language that are not easily addressed with this technique. As such, our results can only reveal relatively long-term changes of brain activity in response to listening to specific sound categories, and our conclusions will benefit greatly from other methods with high temporal resolution, such as (magneto-) electrophysiological recordings. Finally, although stimuli of all three categories were produced by the same singer, we acknowledge that other acoustic features were not homogenized to control for all acoustic parameters that could potentially differ between categories. While some differences in cortical activity may be explained by these low-level features, our main findings are better explained by higher-level, time-varying acoustic features that are characteristic of each category.Together, these data demonstrate different cortical regions that are preferentially modulated by particular sounds, whether they are music, speech or a mixture of the two. However, the anatomical resolution given by the technique does not allow us to distinguish finer anatomical details regarding the specific distribution of the statistical maps. For the same reason, we can not elaborate a more detailed analysis regarding the participation of the primary auditory cortex in planum polare and temporale, and SMA), being particularly sensitive to the temporal structure and acoustical properties of music subjected to further processing beyond the primary auditory cortices.Our data indicates that music selectivity in distributed brain regions independently of using vocal music with and without lyrics. Music-sensitive regions involved frontal and temporal cortical areas, specially in the right hemisphere. Our results indicate that the temporal structure of vocal music and speech is processed in a large temporal-frontal network, and that speech and music processing diverge, with specific regions , participated in this study. Seventeen volunteers were non-musicians , who had not received extra-curricular music education beyond mandatory courses in school. Musicians  had received at least 3 years of formal training/studies in music (either instruments or singing) and were currently involved in musical activities on a daily basis . Groups Hum, Song, Speech, and their scrambled counterparts . Additionally, 5 blocks of silence (each lasting 15 seconds) were interspersed throughout the stimulation paradigm. The stimulation protocol had a total duration of ~10 minutes.The vocal music paradigm used a pseudo-randomized block design; each block lasted 15 seconds and included 5–7 stimuli from the same category , panel AThe stimulation paradigm was presented with E-prime Study Software  binaurally through MRI-compatible headphones  that attenuated acoustic interference (~20 dB) generated by the gradients. While not used as a formal test for normal hearing, we performed a short audio test (1 min) inside the scanner, using similar stimuli, to evaluate whether volunteers could hear and recognize the different sounds inside the scanner; the volume was deemed comfortable but sufficiently high to mask the noise generated by the imaging acquisitions.Subjects were instructed to pay attention to the stimuli and to press a button with the index finger of their right hand every time they heard a pure tone , which was presented 5 times randomly throughout the paradigm. We used this strategy to ensure attention throughout the stimulation paradigm, and we used a pure tone as it is clearly different from the rest of our stimuli and therefore easily recognizable. Subjects kept their eyes open during scanning.Vocal-music paradigm , who did not participate in the main experiment, rated the emotional valence  and the complexity of each stimulus. Finally, we selected for use in the imaging experiments the 35 sentences considered the most neutral and simple, both in their grammatical structure and meaning .All stimuli . This procedure retained low level acoustical attributes  but rendered the stimuli unintelligible by disrupting their temporal organization  and therefore, their high-level perceptual and cognitive properties. The scrambled counterparts of each of the original sound categories are identified as: 4) Hum-S, 5) Speech-S and 6) Song-S.2, matrix size = 128×128 (voxel size = 2×2×3 mm3), TR = 3000 ms, TE = 40 ms. To improve image registration we also acquired a 3D T1-weighted volume with the following characteristics: voxel size = 1×1×1 mm3, TR = 2.3 s, TE = 3 ms. The total duration of the experiment was 18 minutes. All imaging data are freely accessible at https://openneuro.org/datasets/ds001482.All images were acquired at the National Laboratory for Magnetic Resonance Imaging using a 3T Discovery MR750 scanner  with a 32-channel coil. Functional volumes consisted of 50 slices (3 mm thick), acquired with a gradient-echo, echo-planar imaging sequence with the following parameters: field of view (FOV) = 256×256 mmfsl tools . Images were corrected for movement and smoothed using a 5-mm FWHM Gaussian kernel; spatial normalization was performed using the MNI-152 standard template as reference. fMRI data analysis was conducted using FEAT  version 6.00. Statistical analysis was performed using the general linear model. For each subject  the three original acoustic categories were modeled as explanatory variables (EV), along with their three scrambled counterparts . Target stimuli were included as a nuisance regressor. Statistical maps of between-category differences for each subject were generated using a fixed-effects model, and the resulting contrasts were entered in a random-effects model for between-subject analyses using FLAME [Anatomical and functional images were preprocessed using ng FLAME ,79; musing FLAME  to correversus scrambled stimuli):Analysis 1 :Analysis 2  and spectral (e.g. pitch modulation) content. The contrasts included were: 2.1 Song>Song-SvsSpeech>Speech-S; 2.2 Speech>Speech-Svs. Song>Song-S.versus Speech)Analysis 3 vs. (Speech>Speech-S); 3.2 (Speech>Speech-Svs. (Hum>Hum-S).versus Song)Analysis 4 vs. (Song>Song-S); 4.2 (Song>Song-S)vs. (Hum>Hum-S).versus non-musicians):Analysis 5 vs. (Speech>Speech-S) | musicians > non-musicians; 5.2 (Speech>Speech-S)vs. (Song>Song-S) | musicians > non-musicians; 5.3 (Hum>Hum-S)vs. (Speech>Speech-S) | musicians > non-musicians; 5.4 (Speech>Speech-S)vs. (Hum>Hum-S) | musicians > non-musicians: 5.5 (Song>Song-S)vs. (Hum>Hum-S) | musicians > non-musicians; 5.6 (Songvs. Hum) | musicians > non-musicians.Analysis 6 : Finally, we also performed an independent ROI (region of interest) analysis of the planum polare, planum temporale and Heschl's gyrus. ROIs were derived from the Harvard-Oxford Probabilistic Anatomical Atlas thresholded at 33%; statistical significance threshold was set at p< 0.0028, considering eighteen comparisons were performed . This analysis explored BOLD signal modulations to melodic and non-melodic vocal sounds in three different auditory regions.S1 FigSongvsSpeech; Middle panel HumvsSpeech; and Right panel shows shows SongvsHum. Color codes are similar to Figs Left panel shows (TIF)Click here for additional data file.S2 FigHorizontal bars represent the median; black boxes show the interquartile range; vertical lines show the data range excluding outliers (dots).(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Pharmacotherapy is effective in reducing the core symptoms of attention-deficit/hyperactivity disorder (ADHD). We aimed to investigate the concurrent association between pharmacotherapy for ADHD in offspring and depression-related specialty care visits by the parents with a history of depression.Using data from a variety of Swedish national registers, we conducted a cohort study with 8-year follow-up of 5605 parents (3872 mothers and 1733 fathers) who had a history of depression and an offspring diagnosed with ADHD. The hazard rate for parental depression-related specialty care visits during exposed periods when the offspring was on medication for treatment of ADHD was compared with the hazard rate during unexposed periods when the offspring was off medication. Within-individual comparisons were employed to control for time-constant confounding factors.Among mothers, the crude rates of depression-related specialty care visits during exposed and unexposed periods were 61.33 and 63.95 per 100 person-years, respectively. The corresponding rates among fathers were 49.23 and 54.65 per 100 person-years. When the same parent was compared with him or herself, fathers showed a decreased hazard rate for depression-related visits during exposed periods when the offspring was on medication for treatment of ADHD as compared to unexposed periods . No statistically significant associations were observed in mothers.Among parents with a history of depression, pharmacotherapy for ADHD in offspring is concurrently associated with a decreased rate of depression-related specialty care visits in fathers but not in mothers. Future research with refined measures of parental depression and other time-varying familial factors is needed to better understand the mechanisms underlying the association. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting both children and adults –3. InattA multi-country online survey conducted among 2326 caregivers of children/adolescents with ADHD showed that the caregivers experienced considerable burden in terms of work, social activity, family life, and parental stress, despite pharmacotherapy received by all children/adolescents during the previous 6 months . In addiHigh caregiver burden has been linked to depression among caregivers of patients with different health problems –12. PrevOne substantial challenge to such investigation results from the genetic overlap between ADHD and depression. The most up-to-date meta-analysis of genome-wide association studies (GWASs) of ADHD reported a moderate genetic correlation (about 0.4) between ADHD and depression . BecauseUsing data from the Swedish national registers, we conducted a cohort study to investigate the concurrent association between pharmacotherapy for ADHD in offspring and rate of depression-related specialty care visits by the parents with a history of depression.All residents in Sweden are assigned a unique personal identity number that allows for large-scale linkage across the Swedish national registers . The MedInternational Classification of Disease, 10th, revision (ICD-10 code: F90). We then identified their parents who were born from January 1, 1964 onwards and had at least one specialty care visit with depression as the primary diagnosis. In the current study, while the offspring defined the exposure , the parents constituted the cohorts. In total, we identified 3872 mothers and 1733 fathers fulfilling the inclusion criteria. Mothers and fathers were separately followed up for future depression-related visits from January 1, 2006, the offspring’s 6th birthday, or the first depression-related visit, whichever came last, until death, death of the offspring, the offspring’s 18th birthday, or December 31, 2013, whichever occurred first. All offspring were at least 6 years old when their parents entered the follow-up, because ADHD medications are only recommended for children at least 6 years old in Sweden  age at baseline: 36.1 [5.1] years), 4194 and 8784 outcome events occurred during 6838 exposed and 13,735 unexposed person-years, giving crude rates of 61.33  and 63.95  per 100 person-years for the respective periods. Among 1733 fathers (Mean [SD] age at baseline: 37.4 [4.9] years), 1532 and 3187 outcome events occurred during 3112 exposed and 5832 unexposed person-years, giving crude rates of 49.23  and 54.65  per 100 person-years for the respective periods. Other baseline characteristics of parents and their offspring are shown in Table Between-individual comparisons Table  showed nWhen the same parent was compared to him or herself across different time periods Table , fathersThe pattern of results from both between- and within-individual comparisons remained in sensitivity analyses in the three sub-cohorts of depressed parents, using two alternative definitions of on-medication period, or using depression-related unplanned visits as the outcome events Table .Table 3SFinally, despite some fluctuation, the rate of depression-related visits during 40 weeks before ADHD treatment initiation in children appeared to be stable in both mothers and fathers. After treatment initiation, the rate in mothers remained relatively stable; the rate in fathers decreased within 16 weeks, nearly leveled off afterwards until it decreased again after approximately 32 weeks  with a history of depression and an offspring diagnosed with ADHD for 8 years to investigate the concurrent association between pharmacotherapy for ADHD in offspring and rate of depression-related visits in parents.Between-individual analyses yielded no difference in the hazard rate for depression-related visits in parents during exposed periods when their offspring were on medication for treatment of ADHD as compared to unexposed periods. Nonetheless, the analyses could not take into consideration individual specific baseline severity of depression, and other unmeasured time-constant or time-varying factors. In within-individual analyses, we compared the same parent across time periods when his or her offspring was on and off medication for treatment of ADHD. Only those parents who had at least one outcome event during follow-up and whose offspring had both on-and off-medication periods contributed to the analyses. Within-individual comparisons helped rule out bias arising from time-constant factors, such as genetic makeup and disease severity at baseline, and thus provided more valid estimates than between-individual comparisons. Based on within-individual comparisons, we detected an association between pharmacotherapy for ADHD in offspring and a decreased hazard rate for depression-related visits in fathers. No statistically significant association was observed in mothers. The pattern of results remained in all sensitivity analyses, suggesting the findings were not due to our definitions of study cohort, exposure, or outcome event.In the current study, we speculate that the change in hazard rate for depression-related visits in parents might to some extent reflect the change in severity of depression during exposed and unexposed periods. Our findings then could be explained by proper management of ADHD in offspring leading to decrease in severity of depression in the fathers. The process might be mediated by father-perceived improvements in children’s ADHD and subsequent stress-relief, as proposed by two prior clinical studies reporting parent-perceived improvements in children’s ADHD-related behavioral symptoms, parenting stress, and depressive symptoms in parents following methylphenidate treatment for ADHD in the children , 34. AltTo examine whether the observed associations for fathers were due to reverse causation , we plotted the rates of depression-related visits by parents per every 8 weeks during 40 weeks before and 40 weeks after treatment initiation in offspring. We observed no obvious drop in the rate shortly before treatment initiation either in mothers or in fathers, suggesting that treatment initiation in offspring was unlikely triggered by parents being less depressed. Nonetheless, we cannot rule out the possibility that decrease in severity of depression in fathers might help improve their offspring’s compliance to treatment of ADHD. More research is needed to unravel the role of the complex and dynamic parent-offspring interactions in the associations under study.The main strengths of our study include the large sample and prolonged follow-up, both enhancing the statistical power for detecting small effects. The Multi-Generation Register allowed unambiguous identification of parent-offspring relations. The prospectively collected data on medication dispensations and depression-related specialty care visits precluded recall bias. Furthermore, we employed an innovative within-individual comparison design to control for unmeasured time-constant factors that often threaten the validity of observational studies. In addition, since the exposure and outcome events were separately defined in offspring and their parents, our study was not subject to bias due to confounding by contraindication  .We also acknowledge some limitations of the study. First, we are not aware of any validation study on ADHD diagnosis in the National Patient Register. Nevertheless, a prior study of 19,150 twins in Sweden found that 70% twins with an ADHD diagnosis also screened positive for ADHD by their parents . In the Among parents with a history of depression, pharmacotherapy for ADHD in offspring is concurrently associated with a decreased rate of depression-related specialty care visits by fathers but not in mothers. Future research with refined measures of parental depression and other time-varying familial factors is needed to better understand the mechanisms underlying the association.


Human mesenchymal/stromal stem cells (hMSC) are the most promising cell source for adult cell therapies in regenerative medicine. Many clinical trials have reported the use of autologous transplantation of hMSCs in several disorders, but with limited results. To exert their potential, hMSCs could exhibit efficient homing and migration toward lesion sites among other effects, but the underlying process is not clear enough. To further increase the knowledge, we studied the co-regulation between hypoxia-regulated genes and miRNAs. To this end, we investigated the miRNA expression profile of healthy hMSCs in low oxygen/nutrient conditions to mimic ischemia and compared with cells of patients suffering from critical limb ischemia (CLI). miRNAs are small, highly conserved, non-coding RNAs, skilled in the control of the target’s expression level in a fine-tuned way. After analyzing the miRNOme in CLI-derived hMSC cells and healthy controls, and intersecting the results with the mRNA expression dataset under hypoxic conditions, we identified two miRNAs potentially relevant to the disease: miR-29b as a pathological marker of the disease and miR-638 as a therapeutic target. This study yielded a deeper understanding of stem cell biology and ischemic disorders, opening new potential treatments in the future. Ischemic disorders are characterized by reduced blood flow to a tissue or organ due to unfavorable vascular conditions, generally caused by atherosclerosis, such as stroke, myocardial infarction, and critical limb ischemia (CLI). They share the same etiopathological conditions, and to counteract the progression of the disease, pharmaceutical and surgical approaches have been explored to restore the function of arteries, although they cannot support long-term tissue regeneration and recovery. Thus, alternative approaches have to be considered.Among these, the autologous transplantation of bone marrow-derived mesenchymal/stromal stem cells (MSC) contributes to tissue regeneration due to their multilineage differentiation capacity, immunomodulatory and anti-inflammatory effects, capacity to secrete trophic factors that are able to induce neovascularization and inhibit cell death, as well as their migratory capacity to reach the injured sites .For these reasons, MSCs have become an attractive cell system for clinical applications in different disorders, due to the feasibility of isolation, safety in transplantation, and benefits for patients irrespective of age .Critical limb ischemia is a severe disorder in which the lack of blood flow can cause necrosis and gangrene in the feet and legs, ultimately resulting in limb amputation ,4. Cell-based therapy is increasingly recognized as a promising therapeutic option for patients in which the autologous transplantation of hMSCs is applied to induce angiogenesis and promote the regeneration of ischemic tissues, but with limited results ,6. In faRecently, a gene therapy approach has also been explored, in which genetic material encoding for proteins that may help to increase revascularization is injected into patients, but it showed no clear differences between treatment groups .The failure of these procedures may suggest that either MSC therapeutic mechanisms remain elusive or that the disease condition affects the results. Both of these require further investigation.per se is not sufficient to regenerate vascular damage, although several studies demonstrated that ischemia is able to stimulate neoangiogenesis through HIF1-mediated processes [Tissue ischemia rocesses , to indurocesses , and to rocesses .The homing and migration of transplanted hMSCs are the major challenges to be solved in stem cell-based therapy. These processes have been compared to leukocytes due to their common features, such as cytokine responsiveness and ability for transendothelial migration ,13. A mumiRNAs are short (18–25 nucleotides), highly conserved, non-coding RNAs involved in the regulation of gene expression by binding to mRNA, leading to mRNA degradation or the inhibition of protein synthesis . They reIncreasing attention has been given to secreting miRNAs. Circulating miRNAs have been reported as novel diagnostic or therapeutic targets in several human diseases, based on the analysis of miRNAs isolated from the plasma of patients ,21,22. HTo this end, we assessed the miRNA expression profile of healthy and CLI-derived hMSC cells as a model of ischemic disorders. Multi-omics profiling revealed two miRNAs as important regulators of cell migration: miR-29b as a potential marker of the disease and miR-638 as a potential therapeutic target. To our knowledge, this study is the first to identify the co-regulatory network among the hypoxia-regulated genes and miRNAs in human mesenchymal stem cells (hMSCs), the most promising cell source for cell therapies in regenerative medicine.The main aim of this study was to identify the differential miRNA expression profile between healthy hMSC cells (CTRL) and those derived from CLI patients (CLI), trying to understand the defective molecular mechanisms underlying a pathological condition. We used hMSC cells for their involvement in reparative processes in vivo. The clinical characteristics of these cells are reported in t-test (2) or in hypoxic (0.5% O2) and serum-starved (0.5% FBS) conditions, to mimic pathological ischemia (referred as hypoxia), in which a lack of oxygen and nutrients is present .A principal-component analysis (PCA) revealed that healthy hMSCs and CLI-derived hMSCs were clearly separated . We thent-test , compari2 + 0.5% FBS) and in CLI-derived cells (2 + 0.5% FBS). A further upregulation of miR-29b (three-fold) was seen when CLI cells were exposed to 0.5% O2 + 0.5% FBS , and validated data from TarBase and miRecords.A total of 907 predicted targets of miR-29b with HIT ≥ 3 criteria were found .2 for 24 h by GEO2R (GSE55875) [p-value <0.01), showing an enrichment in the ECM–receptor interaction pathway , and in the collagen and cadherin protein domain  in stemness  . Intersestemness .According to miR-29b downregulation, we selected 1940 upregulated genes in CTRL cells in the hypoxia condition (FC LOG2 ≥ +2). Comparing them with 907 predicted miR-29b target genes, we identified 23 gene hits showing a direct inverse correlation with miR-29b expression B,C. InteAltogether, these data hint at a direct role of miR-29b in the regulation of hypoxic gene expression, specifically in the pathological condition and cell migration. Among the retrieved putative targets, we looked for genes belonging to these pathways , and we compared and contrasted the expression of genes in healthy and CLI cells. We validated miR-29b predicted targets by quantitative real-time PCR A–D. RT-PDe facto, miR-638 is upregulated in CLI NORMOXIA cells (FC = 0.836), but the hypoxia condition restores the expression to the CTRL NORMOXIA level (CLI HYPOXIA/CLI NORMOXIA FC = −1.08).On analysis of the miRNA expression profiles of CLI-derived cells exposed to hypoxia (CLI HYPOXIA) compared to normoxia (CLI NORMOXIA) cells, we found three differentially expressed miRNAs A FC ≥ ±B. This uThis peculiar expression was allowed to proceed to target prediction using the miRSystem database (HIT≥3) and GE comparison, as previously described. In These findings suggest that miR-638 could be a therapeutic miRNA, providing new insights into the understanding of the pathogenesis of CLI, but also suggesting novel, putative targets for therapeutic approaches.in vitro and pre-clinical studies, MSC-based therapy has reached the bedside as a new therapeutic option to treat severe diseases in clinics. Since 2010, more than 50 clinical trials have been conducted using MSC cell therapy due to its multilineage differentiation capacity, immunomodulatory and anti-inflammatory effects, homing and migratory capacity to injured sites. However, the efficiency of MSC therapy is rather low, an there is insufficient evidence to support cell therapy in clinical practice [Based on multiple practice ,30,31.To date, the mechanisms by which autologous transplantation improves clinical outcomes in patients with ischemic disorders such as CLI indicate that hMSCs have the capacity to stimulate the formation of new blood vessels either by stimulating endothelial cell proliferation and migration , by secrThe combination of these mechanisms led to the amelioration of tissue perfusion, but limited results were observed in clinical trials due to poor cell engraftment, short cell persistence after transplantation, and a low survival rate , all proIn this study, we used an -omics approach to identify deregulated miRNAs in hMSC cells exposed to conditions mimicking the pathological feature of ischemic disorders i.e., lack of oxygen and nutrients. As a result of our analysis, we retrieved miR-29b as a potential pathological marker of ischemia, due to the negative effect on the hypoxia signaling genes and ECM protein synthesis when upregulated. HIF3A, VEGF and PHD2 are all involved in hypoxic response . We recePublished data has already reported that the upregulation of miR-29b has been involved in inhibiting angiogenesis. The ectopic expression of miR-29b inhibits HUVEC cells from forming three-dimensional capillary-like tubular structures, cell proliferation and migration . In addiBy bioinformatic and RT-PCR analysis, we revealed that miR-29b could regulate the expression levels of metalloproteinase (MMP-2 and MMP-8) and collagen genes . The MMP enzymes are a family of zinc-dependent endopeptidases that degrade various proteins in the extracellular matrix (ECM), including collagen, and alteration of this process could influence vascular remodeling .Published in vitro studies showed that the overexpression of miR-29b significantly decreased the mRNA and protein level of MMP2 and the activity of MMP2 to suppress gastric cancer cell migration .Therefore, our analysis suggests that the possible failure of vascular remodeling observed in CLI patients could be mediated in part by the down-regulation of genes involved in hypoxia signaling  and ECM protein synthesis  via miR-29b . In addiOn looking for a therapeutic marker, we found that miR-638 expression showed an inverse correlation comparing the normal and pathological conditions. It has been reported to be involved in MSC functions such as cellular proliferation, differentiation, migration, and cell death . DecreasTherefore, our analysis reveals that the down-regulation of miR-638 occurring in hypoxia could affect cell migration.Although preclinical studies have enlarged our knowledge of the pathophysiological mechanisms of ischemic diseases, there is still no validated therapy to successfully treat ischemic tissues. Human MSCs, with their fascinating properties, are used in clinical trials, but we still do not know how to make them more efficient.Here, we used a computational approach starting from miRNA expression in hMSCs to identify other targets that could be modulated to achieve a therapeutic goal.We believe that our study provides significant novel insights and potential targets for the prevention and treatment of human vascular diseases. n = 2) (III or IV stage of Leriche–Fontaine classification) enrolled for treatment with autologous bone marrow cells transplantation between February 2008 and July 2008. The protocol was approved by the Institutional Ethics Committee of Universita’ L. Vanvitelli of Naples and was registered at the Trial Registration site, NCT00306085. All patients gave written informed consent before evaluation for inclusion in the study  were isolated from patients with end-stage CLI (he study .n = 2), we collected bone marrow aspirate removed from a male who had undergone orthopedic surgery (Ctr#1) which would normally have been discarded, and the other hMSC cell line was purchased from ProVitro AG .For healthy controls (2). Non-adherent cells were removed after 24 h, the adherent cells carefully washed in phosphate-buffer saline (PBS) and further expanded in fresh culture medium. Culture-expanded BMSCs of passage 2–5 were used for miRNA array and quantitative real-time polymerase chain reaction (qPCR). Hypoxic culture conditions were obtained by BD GasPak EZ Anaerobe Gas Generating Pouch System . As certified by the manufacturer, the Anaerobe Gas Generating Pouch System produces an atmosphere containing 10% carbon dioxide and 1% oxygen. Confluent healthy and CLI hMSC monolayers were subjected to normoxic and hypoxic culture for 24 h. Cells were serum-starved in EBM plus 0.5% fetal bovine serum (FBS) at least 8 h before hypoxic culture to minimize the effects of growth factors in the expansion media.A fraction of the 10 mL bone marrow aspirates from the CLI patients subjected to autologous transplantation ,47 was cTotal RNA, miRNA enriched, were isolated and miRNA expression levels analyzed by real-time PCR as described .Real-time PCR was performed using RNA VILO cDNA Synthesis Kit , to convert RNA into cDNA. For a total of 50 ng of cDNA, a 1xSybrgreen PCR Master Mix  was used according to the supplier’s instructions. Primers are listed in miRNoma of the CLI-derived and control hMSCs in hypoxia and normoxia condition were analyzed. Each sample was prepared according to the Agilent’s miRNA Microarray System protocol. Total RNA (100 ng) was dephosphorylated with calf intestine alkaline phosphatase , denatured with DMSO (Sigma), and labelled with Cyanine 3-pCp by T4 RNA ligase . The labelled RNAs were purified and then hybridized to human miRNA Microarray (V1)8x15K  for 20 h at 55 °C with rotation. After hybridization and washing, the arrays were acquired with an Agilent Scanner and data extracted using Agilent Feature Extraction Software, as specified by the manufacturer .t-test. For each p-value, the Benjamini–Hochberg procedure was used to calculate the false discovery rate (FDR) to avoid the problem of multiple testing. The selected miRNA list was obtained using the following thresholds: FDR < 0.05 and abs(ratio) > 2; each value was converted in LOG2. Microarray quality control reports generated by the Agilent Feature Extraction software were used to detect hybridization artefacts. Probe level raw intensity were processed using R/Bio Conductor  and Limmhttp://www.ncbi.nlm.nih.gov/gds) under the accession number: GSE125884.Microarray data were deposited in the Gene Expression Omnibus (GEO) database , pathways (KEGG) and protein interactions (INTERPRO), and gene ontology terms in each of the selected lists was analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) Functional Annotation Clustering tool .


Recent studies have shown that microRNAs (miRNAs) play a role as regulators of neurodevelopment by modulating gene expression. Altered miRNA expression has been reported in various psychiatric disorders, including schizophrenia. However, the changes in the miRNA expression profile that occur during the initial stage of schizophrenia have not been fully investigated. To explore the global alterations in miRNA expression profiles that may be associated with the onset of schizophrenia, we first profiled miRNA expression in plasma from 17 patients with first-episode schizophrenia and 17 healthy controls using microarray analysis. Among the miRNAs that showed robust changes, the elevated expression of has-miR-223-3p (miR-223) was validated via quantitative reverse transcription-polymerase chain reaction (qRT-PCR) using another independent sample set of 21 schizophrenia patients and 21 controls. To identify the putative targets of miR-223, we conducted a genome-wide gene expression analysis in neuronally differentiated SK-N-SH cells with stable miR-223 overexpression and an in silico analysis. We found that the mRNA expression levels of four genes related to the cytoskeleton or cell migration were significantly downregulated in miR-223-overexpressing cells, possibly due to interactions with miR-223. The in silico analysis suggested the presence of miR-223 target sites in these four genes. Lastly, a luciferase assay confirmed that miR-223 directly interacted with the 3′ untranslated regions (UTRs) of all four genes. Our results reveal an increase in miR-223 in plasma during both the first episode and the later stage of schizophrenia, which may affect the expression of cell migration-related genes targeted by miR-223. Therefore, there is an urgent need to elucidate the pathophysiology of the early stages of schizophrenia. Although the exact cause of this disease remains obscure, decades of intensive studies have indicated that various mechanisms of gene regulation, including those employed by noncoding RNAs, participate in the etiology of schizophrenia.Schizophrenia is one of the most common mental disorders, affecting ~1% of the worldwide population. The onset of this disease often occurs during adolescence, and the subsequent chronic course of the illness can become a heavy burden and a serious public health issue4. Emerging evidence has suggested that over 50% of known miRNAs are expressed in the central nervous system, where they play a crucial role in the regulation of neurodevelopment, synaptogenesis, and synaptic function9; this evidence suggests their active involvement in the development of psychiatric diseases. Specifically, recent studies on postmortem brains from patients with schizophrenia have shown alterations in the expression levels of specific miRNAs18. Other studies have reported that circulating miRNAs, which were detected in several body fluids, including serum, plasma, and cerebrospinal fluid, are also influenced by the pathological conditions of many psychiatric disorders, including schizophrenia22. Despite the accumulating evidence described above, the changes in plasma miRNA levels that occur at the initial stage of schizophrenia have not been fully explored.MicroRNAs (miRNAs) are short noncoding RNAs (19–23 nucleotides) that regulate gene expression at the transcriptional and posttranscriptional levels through interaction with the 3′ untranslated region (UTR) of target messenger RNA (mRNA)In the present study, using a global screening approach, the altered expression profiles of miRNAs in plasma from patients with first-episode schizophrenia (FES) were investigated. To further provide a possible molecular explanation for the altered miRNA expression, we also explored the putative target mRNAs of the candidate miRNA.23. Similar to our previous study24, the inclusion criteria for the FES group were as follows: age 15-40 years, no history of antipsychotic medications for psychosis for more than a total of 16 weeks at the time of registration, and continuous psychotic symptoms within the past 60 months. The exclusion criteria included the following: the presence or a history of other neurological illnesses, a traumatic brain injury with any known cognitive consequences or the loss of consciousness for >5 min, a history of electroconvulsive therapy, low premorbid IQ (<70), a history of alcohol addiction, previous continuous illegal substance use  and the presence of clearly diagnosed autism spectrum disorders. For the control group, additional exclusion criteria included any current or previous history of psychiatric disease detected by screening with the modified Mini-International Neuropsychiatric Interview25. Patients in the FES group were evaluated using the Global Assessment of Functioning (GAF) scale23 and the Positive and Negative Syndrome Scale (PANSS)26.A total of 76 Japanese individuals  participated in the present study. In the first set, 17 outpatients who were diagnosed with FES (as described below) and 17 age- and sex-matched control subjects were included Table . The reqThis study was approved by the Medical Research Ethics Committee of the University of Tokyo Hospital . Written informed consent was obtained from all participants.g for 10 min and then stored at −80 °C until use.Peripheral blood samples were drawn by experienced physicians from a peripheral vein. The blood samples were collected between 1 PM and 3 PM after strict fasting for more than 3 h. Within 30 min of blood collection, plasma was isolated via centrifugation at 1200 × Total RNA was extracted from 300 μl of plasma using the 3D-Gene RNA extraction reagent from a liquid sample kit  according to the manufacturer’s specifications. The extracted total RNA was labeled and hybridized onto 3D-Gene Human miRNA Oligo Chips (Toray), which are based on miRBase ver. 19, according to the manufacturer’s instructions. Data were analyzed using GeneSpring GX ver. 12.5 .Global normalization was performed as follows: The raw signal data for each sample were log2-transformed, and the 75th percentiles of the expression values of each microarray were computed. These values were then subtracted from the expression value of each entity independently.After normalization, the miRNAs for which the expression data were detected across all samples were extracted and subjected to statistical analyses.Caenorhabditis elegans miRNA-39 (cel-miR-39) was added to each denatured sample for qRT-PCR analysis. Subsequently, miRNA was transcribed to cDNA using the miScript II RT Kit  and was detected by qRT-PCR using the miScript SYBR Green PCR Kit with a miScript Primer Assay (Qiagen). The relative miRNA expression level was determined by qRT-PCR cycle number with the levels normalized to the average cel-miR-39 transcript level using the ΔΔCT method27.MicroRNAs were extracted from 200 μl of plasma using the miRCURY RNA Isolation Kit - Biofluids  according to the manufacturer’s instructions. For the normalization of sample-to-sample variation, synthetic Stable miR-223-overexpressing cells were selected by G418  from SK-N-SH (human neuroblastoma cell line) cells  transfected with miR-223 overexpression plasmids (Cat# MI000030) or empty plasmid controls (Cat# pCMVMIR) purchased from OriGene . After selection, three single clones from each group were randomly picked and maintained in DMEM with G418. To initiate differentiation, the cells were grown in DMEM containing 10 µM retinoic acid (RA) , 200 µl/ml G418 and 3% fetal bovine serum (FBS) in the dark; conditioned media were replaced every 72 h for 10 days.Neuronal differentiation was morphologically confirmed and validated by Western blot analysis using antibodies against neuron-specific enolase (NSE) , glial fibrillary acidic protein (GFAP) , and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) .P < 0.05 and fold-change > 1.5.Subsequently, total RNA was extracted with the miRCURY RNA Isolation Kit - Cell & Plant (Exiqon). Using 100 ng of total RNA, biotin-labeled complementary RNA was synthesized and hybridized onto a SurePrint G3 Human GE 8 × 60 K v2 Microarray (Agilent Technologies) according to the manufacturer’s instructions. Data were analyzed using GeneSpring GX ver. 12.5 (Agilent Technologies). Briefly, as noted above, raw data were log2-transformed and normalized to the 75th percentile as recommended by the manufacturer. After normalization, only the genes with detection flags present in at least 50% of the samples were extracted and subjected to statistical analyses. To identify significantly downregulated mRNAs, the significance thresholds for unpaired t-tests were set to http://mirwalk.uni-hd.de/)28.For the in silico analysis, the target genes and their miRNA binding site seed regions were predicted using the miRWalk database  using the restriction enzyme pair NheI and SalI. To confirm specific binding to the predicted sites, we prepared another set of fragments with point mutations in the binding sites. These point mutations were introduced with the PrimeSTAR Mutagenesis Basal Kit  following the provided protocol. The mutations were confirmed by sequencing. The primers used in cloning and mutagenesis are listed in Table t-test followed by the Bonferroni correction for multiple comparisons. For qRT-PCR analysis, the expression levels of the candidate miRNAs were compared between patients with FES and controls in the first set using a two-tailed t-test. In the second set, for the purpose of replicating the significant difference identified in the first set, a one-tailed t-test was utilized. Correlations between clinical symptoms and plasma miR-223 levels were assessed with Pearson’s correlation coefficients or linear mixed model analysis. For experiments using miR-223-OE cells, the statistical significance was determined by Student’s t-test for the microarrays and validation, by one-way analysis of variance (ANOVA) followed by Tukey’s honest significant difference test for luciferase assays, and by two-way ANOVA followed by the Bonferroni post hoc test for qRT-PCR analysis. Statistical analyses were carried out using R version 3.4.2 , and a probability value of less than 5% was considered to indicate statistical significance.For the microarray analysis of the first set, statistical significance was assessed using Student’s Demographic characteristics of the subjects included in the first and second sets are shown in Tables P-value < 0.05) between patients with FES and controls , the required sample size was calculated. As a result, 21 patients with schizophrenia (an average of 7.0 years after the onset of the disease) and 21 healthy age- and sex-matched controls were subjected to qRT-PCR analyses, as described in the methods section. The upregulation of miR-223 expression in patients with schizophrenia was confirmed in the replication sample set , while this correlation was not significant in schizophrenia patients in the second set  in patients with FES than in controls , Ras homolog family member B (RHOB), SKI-like proto-oncogene (SKIL) and spectrin repeat containing, nuclear envelope 1 (SYNE1), were defined as candidate target genes because they were detected in both the gene expression and in silico analyses.To further explore the putative target genes of miR-223, an integrative gene expression analysis and an in silico data analysis were performed Fig. . First, To validate the suppression of putative target mRNA expression in miR-223-OE cells, qRT-PCR was conducted to quantitatively evaluate the synthesis of these mRNAs. The expression levels of the four selected mRNAs mentioned above  were significantly decreased before neuronal maturation (day 0), and a significant decrease was also observed 3, 6, and 10 days after RA treatment. Two-way ANOVA showed no interaction between genotype and time after RA treatment. These results are comparable to those obtained from the microarray analysis Fig. .INPP5B, SKIL and SYNE1; however, in RHOB, there are two binding sites, which have previously been reported29  were newly identified in this study.Based on an integrative analysis using both in silico target prediction and the evaluation of gene expression in miR-223-OE cells, four putative target genes, INPP5B is involved in the endocytic and early secretory pathways by regulating the trafficking of biosynthetic cargo, which is strongly related to Lowe syndrome43. One of the neural symptoms of Lowe syndrome is myelin dysfunction, which also contributes to the neural abnormalities in schizophrenia46. In the brain, RHOB, a member of the rho family of GTP-binding proteins, plays a regulatory role in synaptic plasticity and in the migration of neural cells48. SKIL, also known as SNON, is the negative corepressor of the TGF-beta signaling pathway in primary granule neurons49. Previous studies have demonstrated that in postmitotic neurons, SKIL regulates neuron branching, migration and positioning via the modification of axon development, migration, and dendrite morphogenesis52. In addition, SYNE1, also known as Nesprin 1, is associated with the regulation of cell shape and migration by linking the nucleus to the cytoskeleton54. According to a large-scale exome-wide association analysis of schizophrenia, SYNE1 is a high risk gene58. It is striking that these four genes are related to neuronal migration and/or development and are known to be related to the pathophysiology of schizophrenia.59. In particular, it has been suggested that the disruption of miRNA-mediated gene regulation may be involved in schizophrenia-related phenotypes in an animal model of 22q11.2 deletion syndrome.Animal models of schizophrenia have been generated in previous studies by manipulating genes related to the Neuregulin1, Disc1 and 22q11.2 deletion syndrome; all animal models showed neuronal migration abnormalities, which caused neuronal dysfunction similar to that observed in patients with schizophrenia60. For example, miR-34a regulates newborn neuronal function by downregulating several synaptic proteins and receptor subunits and reducing the migration of neuroblasts in vivo61. These results also suggest a possible relationship between the altered expression of miRNAs and the neurobiological changes underlying schizophrenia.To our knowledge, no other studies have reported a significant change in plasma miR-223 levels in schizophrenia. Interestingly, however, several reports using other methods have revealed the abnormal expression of miRNAs, such as miR-130b, miR-193a-3p and miR-34a, which are related to neuronal migration and/or neural development, in the plasma of patients with schizophreniaTaken together, the data suggest the hypothesis that miR-223 may play a role in neural development and neuronal migration via the downstream regulation of genes, which could, in turn, contribute to the etiology of schizophrenia.22. Nevertheless, the results of these studies, including those of the present study, are inconsistent with one another. These discrepancies may be due to differences between sample size or population examined or the application of different technological platforms. Therefore, as noted above, the involvement of miR-223 might be applicable to only a specific subset of patients with schizophrenia. Second, this study used only miR-223-OE cells and did not show a clear relationship between miR-223 and glutamate signaling, although an increase in NR2B and GluR2 levels was previously shown in the hippocampus of miR-223-deficient mice41. Although glutamate receptors are strongly expressed in differentiated SK-N-SH cells62, we were not able to detect any alterations in these receptors. This discrepancy may be due to a difference in signal alterations induced by the deficiency or overexpression of miR-223. Another reason for this finding may be the differences between the analyzed cell types. Nonetheless, research using animal models overexpressing miR-223 will be required to further address this issue.However, the present study has several limitations that need to be acknowledged. First, the present sample size is small, and the replication sample set did not have patients with FES. In this study, as noted above, the average DOI for the first set of patients with FES was <1 year, whereas the average DOI for the second set of patients was ~7 years, suggesting that these two sets are different populations. In addition, due to the lack of samples from patients in remission, we did not evaluate state-dependent changes in the expression of miR-223. Thus, it is necessary for further studies to be conducted on a larger scale, including more patients with FES. In fact, the abnormal expression of plasma miRNA in patients with schizophrenia has been intensively investigated, especially in recent yearsINPP5B, RHOB, SKIL, and SYNE1. Abnormal miR-223 levels may provide clues to the pathophysiology of schizophrenia.In conclusion, through a global expression analysis of plasma miRNA from patients with FES, the present study demonstrates the upregulation of miR-223. Subsequent experimental validation in miR-223-OE cells and an in silico prediction revealed the novel mRNA targets of miR-223: Supplemental Materials


The relation between burden of risk factors, familial coronary artery disease (CAD), and known genetic variants underlying CAD and low-density lipoprotein cholesterol (LDL-C) levels is not well-explored in clinical samples. We aimed to investigate the association of these measures with age at onset of CAD requiring revascularizations in a clinical sample of patients undergoing first-time coronary angiography.1599 individuals  were genotyped  in the Copenhagen area (2010–2014). The burden of common genetic variants was measured as aggregated genetic risk scores (GRS) of single nucleotide polymorphisms (SNPs) discovered in genome-wide association studies.Self-reported familial CAD  was associated with -3.2 years  earlier need of revascularization in sex-adjusted models. Patients with and without familial CAD had similar mean values of CAD-GRS  and LDL-C-GRS . The correlation between the CAD-GRS and LDL-C-GRS was low . In multivariable adjusted regression models, each 1 standard deviation higher values of LDL-C-GRS and CAD-GRS were associated with -0.70 years  and -0.51 years  earlier need for revascularization, respectively.Young individuals presenting with CAD requiring surgical interventions had a higher genetic burden of SNPs relating to LDL-C and CAD , compared with older individuals. However, the absolute difference was modest, suggesting that genetic screening can currently not be used as an effective prediction tool of when in life a person will develop CAD. Whether undiscovered genetic variants can still explain a “missing heritability” in early-onset CAD warrants more research. Coronary artery disease (CAD) begins as a subclinical process, generally spanning several decades before eventually becoming symptomatic. There is, however, a substantial individual variability in age at onset of symptoms and approximately 10% of myocardial infarctions present in young adults . a familiIn this work, we aimed to study the distribution of traditional risk factors and genetic risk variants of CAD and low-density lipoprotein cholesterol (LDL-C) levels in young vs. older patients undergoing first-time coronary revascularization therapy to further our understanding about the role of known genetic variants associated with CAD and LDL-C levels, respectively, in premature CAD.The data, analytic methods, and study materials can be made available to other researchers for purposes of reproducing the results or replicating the procedure upon request (through collaboration). The Copenhagen Cardiovascular Genetic study (COGEN) is a biobank that has collected superfluous whole blood from patients admitted to six cardiology departments in the Capital region of Copenhagen from 2010–2017. COGEN currently contains samples from ~80,000 individuals. Since all permanent residents hold a Danish identification number, these data can be linked with various clinical databases at an individual level. To date, a sample of ~5200 individuals from COGEN who have had at least one coronary angiogram performed between 2010–2014 have been genotyped as described below and in the online supplemental.Data on the angiograms were collected from the Eastern Danish Heart Registry, which is a clinical database, where information on demographic , risk factors and comorbidities , and coronary pathology has been routinely entered on all patients in the Eastern region of Denmark. InformatFor the current investigation, we included those patients who had no prior known CAD and who were found to have significant CAD requiring interventions by angioplasty or coronary artery bypass surgery. We defined premature cardiovascular disease as a first-event occurring before age 55 years in men and 65 years in women, in agreement with prior studies. In additHRC version r1.1).[S1 File for detailed information on QC and imputation.Genome-wide genotyping was performed using the Illumina Infinium Human CoreExome BeadChip  and updated to build 37 (i.e. hg19). We employed a standard quality control (QC) pipeline after which a total of 5128 individuals and 539004 SNPs were available for further analyses (of which the majority were not first-time interventions). We then imputed the data on the Sanger Imputation Server to the first release reference panel of human haplotypes by the Haplotype Reference Consortium (on r1.1). See S1 F. We constructed 2 different risk scores, by orienting the SNPs such that the risk increasing allele was always coded as the alternative allele and the risk decreasing allele as the reference allele, regardless of allele frequency. In the unweighted GRS (uGRS), we assigned 1 point per risk increasing allele assuming an additive risk model. GRSi is the unweighted GRS for individual i, sij is the number of effect increasing alleles for the j’th SNP for individual i and N is the number of SNPs in the GRS:Based on data from prior genome-wide association studies of individuals of European ancestry, we compiled additive and weighted genetic risk scores (GRS) for CAD and LDL-C. Overall, 67 and 58 independent single nucleotide polymorphisms (SNPs) previously identified from genome-wide association studies were included for the CAD and LDL-C risk scores, respectively. Full SNP lists are available in i is the weighted GRS for individual i, sij is the number of effect increasing alleles for the j’th SNP for individual i, N is the number of SNPs in the GRS and βj is the reported effect size for the j’th SNP.In the weighted GRS (wGRS), the risk alleles were weighted according to beta-estimates derived from the prior genome-wide association studies. Thus, fo2>0.8), S1 Table. Similar, for low-density lipoprotein cholesterol (LDL-C),[2>0.8), S2 Table. Eligible proxy variants were identified using https://analysistools.nci.nih.gov/LDlink/.Of the CAD related SNPs, 51 were directly genotyped and 16 additional SNPs were available through statistical imputation, of which 3 SNPs were proxy variants (r (LDL-C),, 14 43 SCharacteristics of the overall sample and various age-groups are presented as mean values ± standard deviation (SD) for continuous variables and as number (percentage) for discrete variables. Tests for trends across the four age-groups were performed by the Cochran-Armitage trend test for discrete variables and by general linear models  for continuous variables.Fig 1) and multivariable  linear regression models. A two-sided p-value <0.05 was considered as statistically significant. All analyses were performed in SAS version 9.3 .We estimated the association of GRS with age at onset of disease by linear regression models, where age at onset (as a continuous variable) was included as the dependent variable and GRS, principal components 1 and 2, and sex as the independent variables. To facilitate the comparison, GRS were standardized to mean 0 and SD 1 before analyses. We also estimated the association of the other variables with age at onset by similar univariable  approved the project and COGEN has permission from the Data Protection Agency (00916 GEH-2010-001).Tables 2 show the full characteristics of the sample for men and women, respectively. The proportion of patients who had familial CAD, were more frequently smokers, and the mean values of LDL-C-GRS and CAD-GRS were higher in young vs. older among both men and women, Tables 2. However, for the youngest women (<50 years) GRS values appeared less elevated compared with men and older women. Except for the oldest ages, the proportion with known high cholesterol levels increased with advancing age, whereas the burden of LDL-C-GRS decreased. Diabetes and hypertension prevalence and body mass index values were also higher with older ages.We identified a total of 1,599 patients of Danish ancestry  undergoing first-time revascularization with available genotyping. The mean age was 64 years (min-max 29–96 years) and 28% were women. Familial CAD was reported by 41% of the study population. Patients with familial CAD had non-statistically significantly different mean values of CAD-GRS  and LDL-C-GRS , compared with patients without familial CAD. The correlation coefficients between the unweighted CAD-GRS and unweighted LDL-C-GRS were low .Fig 1. Similar, for each 1 standard deviation high CAD-GRS or LDL-C-GRS, age at revascularization was lowered by approximately 0.5 years, although estimates did not reach statistical significance for CAD-GRS, Figs 2. There was no evidence of effect modifications of the two GRS by smoking, familial CAD, BMI, or gender (p for interactions >0.10).Adjusted for sex, familial CAD was associated with 3.2 years of earlier presentation of CAD, compared with no familial CAD, Tables 2. Mean CAD-GRS and the prevalence of familial CAD tended to be similar or lower in STEMI versus the other presentations, Table 3. Mean LDL-C-GRS levels were also comparable between the four CAD presentations.Patients with premature CAD presented more often with STEMI and less often with stable angina, compared with older individuals, In the present work, we investigated the relation between familial CAD and influence of genetic predisposition for CAD and LDL-C with the age at onset of CAD requiring surgical interventions in a clinical cohort of patients referred for angiography and undergoing revascularization as part of usual clinical care. Our principal observations are five-fold. First, we observed that familial CAD was associated with 3 years earlier onset of disease, compared with those without familial CAD. Second, there was no correlation of familial CAD with our genetic risk scores and adjustment for familial CAD did not impact the estimates associated with CAD-GRS / LDL-C-GRS (and vice versa). Third, for each standard deviation higher GRS-CAD, age at onset of disease declined by approximately 0.5 years, but was not statistically significant. Fourth, young patients presented more often with ST elevation myocardial infarction and older patients more often with stable angina. The GRS-CAD values were not very different for these two manifestations of CAD. Fifth, although recognized high cholesterol levels were more common in older vs. younger patients, the genetic burden of SNPs predisposing to high blood LDL-C was higher in young vs. older individuals.Current common SNPs have been estimated to explain only ~11–13% of the heritability of CAD., 16 In lSomewhat counterintuitively, we observed that several of the traditional risk factors for CAD, including diabetes, hypertension, known high cholesterol levels, and levels body mass index were higher in those presenting at older age, compared with young individuals. These risk factors tended therefore to be associated with greater age at onset of CAD. Although the observations may be true , the paradox could also be well explained if all individuals had equally adverse risk factors and just some individuals had been diagnosed and treated (since treatment postpone onset of CAD). Yet, it is also well known that body mass index, physical inactivity levels, blood pressure, and blood cholesterol levels increases longitudinally with ageing, making the results quite expected. For the Although we observed that those with higher CAD-GRS and LDL-C-GRS presented at younger age, the absolute difference in years were modest , suggesting that even if GRS may be of some use in risk stratification in a primary preventive setting (as suggested by prior studies),, 7, 26 iInterestingly, women presenting at a very young age had a lower burden of genetic variants associated with the risk of CAD and LDL-C levels than those presenting in mid-life, suggesting that other mechanisms may underlie the development of CAD requiring surgical interventions in very young female individuals. Indeed, normal arteries, coronary artery thrombus, dissection, vasculitis, and coronary anomaly are collectively more common causes than atherosclerotic disease in young women presenting with suspected CAD.The major strength of our study included the rather large and clinically representative sample of patients undergoing first-time coronary artery revascularization. Data were, however, collected in a clinical setting and some of it was based on a self-reported history, including the definition of familial CAD, diabetes, and known high cholesterol levels. This may have led to underreporting  of various disorders. Especially young individuals may not have been adequately screened for risk factors, including diabetes, hypertension, and high blood cholesterol levels prior to presenting with CAD in the coronary artery unit, which may have influenced our observations. Risk time for family members may also have been lower in young patients, which could have contributed to the observed lower prevalence of familial CAD in STEMI vs. the other presentations. It can also not be excluded that some of the young individuals with a high burden of CAD related genes might have died from sudden cardiac death before reaching the catheter room. We did not have data on the indication for revascularization in all individuals. Apart from symptoms of angina or myocardial infarction, some people may have been revascularized because of systolic heart failure , or ventrYoung individuals presenting with CAD requiring surgical interventions had a higher genetic burden of SNPs relating to LDL-C and CAD , compared with older individuals with CAD. However, the absolute difference was modest, suggesting that genetic screening can currently not be used as an effective prediction tool of when in life a person will develop CAD. Whether undiscovered genetic variants can still explain a “missing heritability” in early-onset CAD warrants more research.S1 File(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.