Longitudinal Data Collection Research Articles

Leveraging Single-Case Experimental Designs to Promote Personalized Psychological Treatment: Step-by-Step Implementation Protocol with Stakeholder Involvement of an Outpatient Clinic for Personalized Psychotherapy

Our objective is to implement a single-case experimental design (SCED) infrastructure in combination with experience-sampling methods (ESM) into the standard diagnostic procedure of a German outpatient research and training clinic. Building on the idea of routine outcome monitoring, the SCED infrastructure introduces intensive longitudinal data collection, individual effectiveness measures, and the opportunity for systematic manipulation to push personalization efforts further. It aims to empower psychotherapists and patients to evaluate their own treatment (idiographic perspective) and to enable researchers to analyze open questions of personalized psychotherapy (nomothetic perspective). Organized around the principles of agile research, we plan to develop, implement, and evaluate the SCED infrastructure in six successive studies with continuous stakeholder involvement: In the project development phase, the business model for the SCED infrastructure is developed that describes its vision in consideration of the context (Study 1). Also, the infrastructure's prototype is specified, encompassing the SCED procedure, ESM protocol, and ESM survey (Study 2 and 3). During the optimization phase, feasibility and acceptability are tested and the infrastructure is adapted accordingly (Study 4). The evaluation phase includes a pilot implementation study to assess implementation outcomes (Study 5), followed by actual implementation using a within-institution A-B design (Study 6). The sustainability phase involves continuous monitoring and improvement. We discuss to what extent the generated data could be used to address current questions of personalized psychotherapy research. Anticipated barriers and limitations during the implementation processes are outlined.

What Factors Predict Adaptive Functioning in Preschool Children with Autism Spectrum Disorder? A Longitudinal Study.

Adaptive functioning constitutes a fundamental aspect of the phenotype associated with autism spectrum disorder (ASD) in preschool-aged children, exerting a significant influence on both the child and the family's overall quality of life. The aim of this study was to investigate the predictors of the adaptive functioning domains in preschool-age children with ASD at two time points, providing a snapshot of this fundamental developmental step. Methods: Ninety-five children with ASD (M = 3.89, SD = 1.13) were included in the study and longitudinal data (the mean length of the longitudinal data collection was 1 year) on ASD features such as social communication and social interaction, repetitive and restricted behavior, cognitive level, and adaptive functioning were collected. We considered autistic features, cognitive level, and sociodemographic factors as possible predictors of the different adaptive functioning domains one year later. Results: Data obtained showed a worsening of the ASD features and adaptive functioning after one year. Furthermore, the severity of repetitive and restricted behavior predicted adaptive functioning, especially in the social and practical domains of the child, one year later. This prediction was observed alongside the child's cognitive level. Conclusions: The study identifies some potential predictive factors of specific adaptive functioning domains in preschoolers with ASD. Considering how critical adaptive functioning is for the well-being of both the child and their family, it becomes imperative to design early-stage interventions focused on nurturing adaptive skills in children with ASD.

Risdiplam in Spinal Muscular Atrophy: Safety Profile and Use Through The Early Access to Medicine Scheme for the Paediatric Cohort in Great Britain.

Spinal muscular atrophy (SMA) is a progressive neuromuscular disease caused by mutations in Survival motor neuron 1 (SMN1) gene, leading to reduction in survival motor neuron protein (SMN), key for motor neuron survival and function in the brainstem and spinal cord. Risdiplam is an orally administered SMN2-splicing modifier which increases production of functional SMN protein. Risdiplam was offered in the UK under early access to medicines scheme (EAMS) to SMA type 1 and 2 patients aged 2 months and older, not suitable for authorised treatments from September 2020 to December 2021. To describe the largest paediatric European real-world set of data on patients' characteristics and short-term safety for risdiplam in Great Britain through EAMS. We collated data from SMA REACH UK a national clinical and research network for all patients enrolled onto EAMS and assessed all submitted adverse events. Of the 92 patients; 78% were Type 2 SMA, mean age 10.9 years, range 0-17 years. 56 were treatment naïve, 33 previously treated; of these 25 had received nusinersen, 3 previous treatment unknown. Sixty adverse events (AEs) were reported occurring in 34 patients. The commonest were respiratory tract infections and gastrointestinal disturbance. Four life-threatening events were reported with 2 deaths and permanent cessation of risdiplam in 3 patients.Overall, 38/60 AEs were considered unrelated to risdiplam, 10/60 related to risdiplam and for 12/60 causality not specified. This study found a safety profile similar to clinical trials with no new safety concerns identified. With the restricted eligibility of onasemnogene abeparvovec and complications of nusinersen administration, EAMS allowed access or continued treatment to naïve patients or patients no longer suitable for approved medications. Collection of longitudinal data for this complex population is needed, to provide greater insights into risdiplam's role in addressing patients' needs into the future.

Management of treatment resistance-Treatment-resistant schizophrenia

Despite avery high prevalence and substantial impairments among affected individuals, treatment-resistant schizophrenia (TRS) has not been sufficiently researched in clinical research in the field of psychiatric disorders and the pathophysiology is still poorly understood. Abetter clinical and pathophysiological understanding of this heterogeneous and severely affected population of people with persistent symptoms in different domains is necessary in order not only to be able to intervene early but also to develop novel therapeutic strategies or individualized treatment approaches. This review article presents the state of the art criteria of the pharmacological TRS, neurobiological disease models and predictive factors for TRS as well as the phenomenon of pseudo-treatment resistance and the clinical management of TRS. In the future, not only the use of operationalized criteria and definitions of TRS in longitudinal studies and randomized-controlled trials (RCTs) are paramount, but also the observation of trajectories with the integration of multimodal longitudinal phenotyping and the longitudinal collection of clinical routine data in academic research, which will be possible in the newly created German Center for Mental Health (DZPG).

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Registers as central real world data source: the experience of the Italian Multiple Sclerosis and Related Disorders Register

Registers collecting data from clinical practice (real world data) have gained increasing interest in recent years in the scientific, administrative, and regulatory fields. The value of longitudinal data collection in deepening knowledge about a specific pathology and its healthcare complexity is increasingly recognized. This article describes the development, organizational structure, and technical characteristics of the Italian Multiple Sclerosis and Related Disorders Register (RISM). This multicentre and prospective study gathers demographic, clinical, and epidemiological data from the Italian population with multiple sclerosis and related diseases. The study, officially launched in 2015, but containing data collected since the 1990's, currently involves the active participation of 136 specialized clinical centres and more than 80,000 enrolled patients. The analysis of data in RISM allows for a detailed description of the characteristics of multiple sclerosis and related diseases, providing new insights useful for healthcare planning, cost evaluation, treatment efficacy and safety assessment, and scientific research studies. The main demographic and clinical data of enrolled patients are reported, with a focus on specific study cohorts. In a continuous effort to improve data quality, RISM has implemented specific quality indicators. Starting from the RISM experience, crucial aspects such as the institutional recognition of the disease register, the contribution that register can provide in pharmacovigilance studies, the organizational and management challenges, and privacy issues are discussed.

Testing the feasibility of mobile ecological momentary assessment for symptom burden and management among metastatic cancer patients.

Individuals who have metastatic cancer experience substantial physical and psychological distress (e.g., pain, depression, anxiety) from their disease and its treatment compared to patients with less advanced disease. As the burden of symptoms varies over time, ecological momentary assessment (EMA) may be used to better understand patients' symptom trajectories, complimenting traditional longitudinal data collection methods. However, few have used EMA in patients with metastatic disease. The current study adds to the existing literature by exploring interrelated, common cancer-related symptoms of pain, anxiety, and depression and use of cannabis-based products, opioid medications, other (nonopioid) pain medications, and medications for anxiety or depression. An eight-day prospective observational feasibility study was conducted among 50 patients with metastatic cancer recruited from seven solid cancer clinics at The Ohio State University Comprehensive Cancer Center. Participants completed a week of interval-contingent mobile EMA, administered daily at 9 a.m., 3 p.m., and 8 p.m., and a comprehensive interviewer-administered questionnaire on Day 8. Participants were queried on their symptom burden and management strategies (i.e., use of medications and cannabis). We considered EMA to be feasible if a priori retention (80%) and adherence goals (75%) were met. Seventy-nine percent of eligible patients contacted enrolled in the study (n = 50 of 63). Among those enrolled, 92% were retained through Day 8 and 80% completed >90% of EMAs, exceeding a priori objectives. Participants' average pain, anxiety, and depressive symptoms across the week of EMA ranged from 1.7 to 1.8 (1 to 5 scale). Symptoms varied little by day or time of administration. On Day 8, significant proportions of participants reported past-week use of medications and cannabis for symptom management. Participants exceeded a priori adherence and retention objectives, indicating that mobile EMA is feasible among metastatic cancer patients, addressing a gap in the existing literature and informing future research. Restricting eligibility to participants with a minimum cutoff of symptom burden may be warranted to increase observations of symptom variability and provide opportunities for future health interventions. Future research is needed to test the acceptability and quality of data over a longer study period in this patient population.

Feasibility of "Symptom Discovery," a Longitudinal and Comprehensive Data Collection Tool During COVID-19.

There are few patient- or public-facing tools for longitudinal and comprehensive symptom assessment, especially when faced with an uncharacterized condition such as COVID-19 or a chronic condition in which symptoms have not been adequately specified. To address this need, we developed the Symptom Discovery mobile application and tested its feasibility with the US public early in the COVID-19 pandemic. Although there were challenges, results showed feasibility and acceptance.

Mapping the social value creation of renewable energy enterprises in a social open innovation milieu

PurposeAs the backbone of the social open innovation (SOI) system, social enterprises (SEs) are the key drivers of social value creation (SVC). However, at the micro-level, research in this area is lacking, as attention is scantly paid on the comprehensive capabilities of renewable energy enterprises, their industrial heterogeneity and heterogeneous social connections, including bricolage and utility innovation. Drawing from the social resource-based view theory and institutional theory, the research investigates SOI effect on SVC, the moderating role of social ties (ST) and entrepreneurial bricolage (EB) mediation.Design/methodology/approachThe research methodology encompassed several key steps. Initially, a research framework was constructed based on a comprehensive literature review. Subsequently, data were collected by surveying 133 middle to senior-level managers. To assess the proposed hypotheses, a structured equation modeling analysis was conducted using a two-stage approach, which involved partial least squares and hierarchical regression techniques.FindingsThe study reveals that SOI affects SVC significantly, and SOI positively impacts EB. Furthermore, political ties strengthen the positive impact of SOI on EB. Moreover, EB positively impacts SVC. Additionally, EB mediates the relationship between SOI and SVC.Research limitations/implicationsFirstly, the measurement of variables relies on a subjective approach. Future research could employ a quantitative comprehensive index evaluation method of assessment, thereby providing additional validation for the authors' findings. Secondly, although cross-sectional data can be utilized to explore the relationships between variables, there may be inherent biases in the results. Therefore, longitudinal data collection in future research would enable the observation of the long-term effects of SOI and EB on SVC and ST. Thirdly, it would be beneficial to examine other potential factors that could contribute to a more comprehensive understanding of the mechanisms linking SOI to SVC.Practical implicationsFirst, the study underscores the significance of EB in the interplay between SOI and SVC. By embracing innovative approaches and fostering collaborations, SEs can harness EB as a powerful tool for achieving their social missions while overcoming resource constraints. Second, it is imperative for managers to foster a conducive environment for SVC within their organizations, characterized by network ties and partnerships. Simultaneously, they should proactively drive ST initiatives and remain attuned to evolving changes in external environmental laws and regulations. Third, the Malagasy government is actively advocating for social interventions and the establishment of social milieus reminiscent of corporate social responsibility.Social implicationsThis study emphasizes the importance of ST and recognizes the pivotal role of EB in generating social value within an ecosystem that supports SOI. SEs can create lasting positive impacts on society (e.g. improving access to electricity) by embracing these principles and collaborating with stakeholders.Originality/valueThese findings serve to enhance the underlying theoretical context of social entrepreneurship, propose nuanced insight into the methodologies for implementing SVC within the context of renewable energy enterprises and make significant contributions to the ongoing progress of research in the domains of open innovation and social entrepreneurship.

Expanding Access to Comprehensive Geriatric Evaluation via Telehealth: Development of Hybrid-Virtual Home Visits

BackgroundIn response to the aging population, the Department of Veterans Affairs (VA) seeks to expand access to evidence-based practices which support community-dwelling older persons such as the Geriatric Resources for Assessment and Care of Elders (GRACE) program. GRACE is a multidisciplinary care model which provides home-based geriatric evaluation and management for older Veterans residing within a 20-mile drive radius from the hospital. We sought to expand the geographic reach of VA-GRACE by developing a hybrid-virtual home visit (TeleGRACE).ObjectivesThe objectives were to: (1) describe challenges encountered and solutions implemented during the iterative, pre-implementation program development process; and (2) illustrate potential successes of the program with two case examples.DesignQuality improvement project with longitudinal qualitative data collection.Program DescriptionThe hybrid-virtual home visit involved a telehealth technician travelling to patients’ homes and connecting virtually to VA-GRACE team members who participated remotely.Approach & ParticipantsWe collected multiple data streams throughout program development: TeleGRACE staff periodic reflections, fieldnotes, and team meeting notes; and VA-GRACE team member interviews.Key ResultsThe five program domains that required attention and problem-solving were: telehealth connectivity and equipment, virtual physical examination, protocols and procedures, staff training, and team integration. For each domain, we describe several challenges and solutions. An example from the virtual physical examination domain: several iterations were required to identify the combination of telehealth stethoscope with dedicated headphones that allowed remote nurse practitioners to hear heart and lung sounds. The two cases illustrate how this hybrid-virtual home visit model provided care for patients who would not otherwise have received timely healthcare services.ConclusionsThese results provide a blueprint to translate an in-person home-based geriatrics program into a hybrid-virtual model and support the feasibility of using hybrid-virtual home visits to expand access to comprehensive geriatric evaluation and ongoing care for high-risk, community-dwelling older persons who reside geographically distant from the primary VA facility.Graphical

Developing and evaluating Compassionate Workplace Programs to promote health and wellbeing around serious illness, dying and loss in the workplace (EU-CoWork): a transdisciplinary, cross-national research project

Background: Most employees will experience serious illness, caregiving, dying and loss (End-of-Life (EoL) experiences) at multiple points throughout their working lives. These experiences impact affected employees but also their colleagues in terms of health and wellbeing, and the workplace as a whole in terms of workplace safety, productivity and labour relations. The impact of EoL experiences on employees means that workplaces are called to play a more active role in providing support for EoL experiences. Aim: To describe how the EU-CoWork (2024–2028) project addresses its main aims to (1) create Compassionate Workplace cultures, practices and policies and improve health and wellbeing for employees dealing with EoL experiences in different national work contexts in Europe; (2) describe and evaluate the process of co-creation and implementation of Compassionate Workplace Programs (CWPs) and how these influence the programs’ outcomes. Design: EU-CoWork employs a facilitated and co-creative Developmental Evaluation approach to the development of 12 tailored CWPs across four European countries (Belgium, Austria, Sweden and Greece). Methods: To evaluate the outcomes and processes leading to these outcomes, a mixed-methods Realist Evaluation methodology is applied, formulating and testing Context-Mechanism-Outcomes configurations and combining longitudinal quantitative and qualitative data collections. Results: EU-CoWork will generate evidence to support an expanded model of occupational health and safety risk factors sensitive to the specific challenges related to employees’ EoL experiences. In doing so, several challenges will have to be navigated: involving employees with EoL experiences while avoiding overburdening them, avoiding tokenistic engagement, managing power differentials, balancing the need for scientific rigour with the flexibility required in co-creation, reconciling different epistemologies and disciplinary traditions and organisational resistance to change. Conclusion: There are potential long-lasting broader societal impacts through the stimulation of open discourse on EoL topics, the reconciliation of work and care, and changes in gendered work and care patterns.

Evaluation of a multicomponent infrastructural and app-based intervention to increase children's active school travel: A multiple methods study in Tāmaki Makaurau/Auckland, Aotearoa/New Zealand

Power Up Schools (Power Up) was a temporary intervention involving a range of activities aimed at increasing children's active school travel (AST) with a focus on physical and social aspects of schools and their surrounding environs. We evaluated the impact of Power Up on children's AST and how multiple stakeholders (children, school representatives, parents, residents) perceived the overall intervention and its components. This was a multiple methods evaluation study with four primary (elementary) schools in Auckland and their wider communities. The study involved longitudinal data collection (daily travel modes reported by children), repeat cross-sectional surveys with parents, single time-point cross-sectional surveys with residents, post intervention focus groups with children and parents, and post intervention interviews with school representatives. Findings showed evidence for increased AST; general support for Power Up by children, parents, and school representatives; mixed support by residents for some components; the importance of considering diverse needs and preferences in future interventions; the need for more comprehensive communication across stakeholders; and the value of streamlining processes for schools and parents. Comprehensive approaches that are embedded within, and accepted by, the wider school community are recommended for sustainable and effective AST interventions.

Development of dietary assessment instruments which can take cultural diversity and dietary acculturation into account: eating in Sweden (‘Mat i Sverige’)

Abstract Since lack of culture-specific foods in dietary assessment methods may bias reported dietary intake, we identified foods and dishes consumed by residents not born in Sweden and describe consequences for reported foods and nutrient intake using a culturally adapted dietary assessment method. Design consisted of cross-sectional data collection using (semi-)qualitative methods of dietary assessment (and national diet survey instrument RiksmatenFlex) with subsequent longitudinal data collection using quantitative methods for method comparison (December 2020–January 2023). Three community-based research groups were recruited that consisted of mothers born in Sweden, Syria/Iraq, and Somalia, with a median age of 34, 37, and 36 years, respectively. Women born in Syria/Iraq and Somalia who had lived in Sweden for approximately 10 years, reported 78 foods to be added to RiksmatenFlex. In a subsequent study phase, 69% of these foods were reported by around 90% of the ethnic minority groups and contributed to 17% of their reported energy intake. However, differences between the three study groups in median self-reported energy intake remained (Sweden 7.19 MJ, Syria/Iraq 5.54 MJ, and Somalia 5.69 MJ). The groups also showed differences in relative energy contribution from fats and carbohydrates, as well as differences in energy intake from food groups such as bread and sweet snacks. We conclude that a dietary assessment instrument containing culture-specific foods could not resolve group differences in reported energy intake, although these foods provided content validity and contributed 17% of energy intake. The dietary habits collected in this study serve to develop new dietary assessment instruments.

Covariate-guided Bayesian mixture of spline experts for the analysis of multivariate high-density longitudinal data.

With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging data play an important role in the advancement of science. Imaging data that measure brain function are usually multivariate high-density longitudinal data and are heterogeneous across both imaging sources and subjects, which lead to various statistical and computational challenges. In this article, we propose a group-based method to cluster a collection of multivariate high-density longitudinal data via a Bayesian mixture of smoothing splines. Our method assumes each multivariate high-density longitudinal trajectory is a mixture of multiple components with different mixing weights. Time-independent covariates are assumed to be associated with the mixture components and are incorporated via logistic weights of a mixture-of-experts model. We formulate this approach under a fully Bayesian framework using Gibbs sampling where the number of components is selected based on a deviance information criterion. The proposed method is compared to existing methods via simulation studies and is applied to a study on functional near-infrared spectroscopy, which aims to understand infant emotional reactivity and recovery from stress. The results reveal distinct patterns of brain activity, as well as associations between these patterns and selected covariates.

Nurturing Infants to Prevent Atopic Dermatitis and Food Allergies: A Longitudinal Study.

Atopic dermatitis (AD) at a young age often precedes the development of food allergies. Although AD affects millions of infants worldwide, prenatal and postnatal risk factors, and their association with the development of food allergies later on, are not fully elucidated. This study seeks to investigate AD epidemiology in infancy and its risk factors, examining early-life factors (both prenatal and postnatal) that could contribute to the later development of food allergies. Between January 2019 and December 2019, 501 infants were included in this prospective cohort study. Longitudinal data collection was performed through maternal interviews, the first one conducted within three days after the delivery and the second within 24 to 36 months after the delivery, encompassing variables such as demographics, family history of atopy, maternal smoking, antibiotic use during pregnancy, the mode of delivery, breastfeeding history, food practices, and greenness exposure within 3 days from delivery, while they were still in the hospital. Maternal smoking during pregnancy (p = 0.001) and an older sibling atopy history (p = 0.03) was significantly linked to AD incidence. Cesarean section delivery (p = 0.04) was associated with a higher risk of food allergies in infants with AD. Having a garden at home correlated with a higher likelihood of AD (p = 0.01), and food elimination without medical guidance (p = 0.02) due to AD correlated with an elevated risk of food allergies. Encouraging timely allergenic food introduction while promoting dietary diversity, rich in plant-based foods, maternal smoking cessation, and professional dietary guidance may help minimize AD and food allergy risk. Future studies should address the role of greenness in the development of AD and food allergies.

Girls and Online Civic Engagement: Why Are They Less Likely to Engage in Political Discussion and Argumentation?

The text summarizes the results of the second wave of research conducted in Poland as part of the ySKILLS project (Horizon 2020), which explored young people’s digital skills and online civic engagement from six European countries. The study aimed to answer research questions about gender differences in digital skills and the forms of civic engagement in which young people participate through digital means. Data were collected through a Quantitative Longitudinal Data Collection method (survey), and the sample consisted of 1,340 Polish students aged 12–17 from twelve primary and secondary schools. The results showed that boys reported higher levels of involvement in online civic engagement than girls, especially in two areas: 1) discussing or commenting onsocial or partial political issues online and 2) joining or following a political group on social networks. Regarding digital skills, students reported higher levels of proficiency incommunication and interaction skills and lower levels in programming skills. Regarding girls’ digital skills, statistically significant differences were noticed in four areas. Boysdeclared having higher digital skills in technological and operational skills, programming skills, and information navigation and processing skills. It is recommended that schools and policymakers implement measures aimed at reducing gender disparities, for instance, by providing girls with increased chances to acquire programming skills or by highlighting to girls the advantages of engaging in online civic activities.

P150: Social media use and well-being with bipolar disorder during the COVID-19 pandemic

Background:Reliable and consistent social support are associated with the mental health and well-being of persons with severe mental illness, including bipolar disorder (BD). Yet the COVID-19 pandemic and associated social distancing measures (e.g., shelter-in-place) reduced access to regular social contacts, while social media use increased concomitantly.Objective:For this study, we had two goals. First we report descriptive information regarding social media use (SMU) by persons with BD during COVID-19 (all platforms). Specific to Facebook, we next developed and tested a hypothesized model in order to identify direct and indirect associations between BD symptoms, social support, loneliness, life satisfaction, and social media use. Responses were collected during the global spread of the Delta variant and prior/concurrent with the Omicron variant, 20 months after the World Health Organization declared COVID-19 a global pandemic.Methods:Over eight weeks, participants were recruited using social media advertising micro- targeted to adults with BD. On average, participants were 53.96 years of age (SD = 13.22, range 20-77 years), they had completed 15.40 years of education (SD = 4.28) and were diagnosed with BD 19.60 years ago (SD = 10.31). Path analysis was performed to develop and test our hypothesized model.Results:Almost all participants (93%) reported having both Facebook and LinkedIn accounts; 91.1% reported regular use of either or both. During the pandemic, most (60.8%) reported accessing social media several times a day; 36% reported using social media more often since the emergence of COVID-19. Specific to Facebook, the model we hypothesized differed somewhat from what emerged. The resulting model suggests that symptoms of depression predict loneliness and inversely, social support and life satisfaction. Social support predicts social Facebook use whereas passive Facebook use predicts life satisfaction. Symptoms of depression emerged as indirect predictors of SMU via social support.Conclusions:Our findings suggest that the operational definition of passive-active SMU requires further analysis and refinement. In contrast to theory, passive Facebook use appears positively correlated with well-being among certain populations. Longitudinal data collection over multiple points is required to identify associations between BD symptoms, social media use and well-being over time.

Challenges of recruitment and biomarkers collection in Caribbean Hispanics

AbstractBackgroundGenetic Studies of Alzheimer’s Disease in Caribbean Hispanics (CH) has been ongoing for over 20 years. Our primary goal was to identify genes in large well‐phenotyped, multiplex families, and sporadic cases and controls. This longitudinal collection of data represents a unique resource for the scientific community. The project is led by collaborators in the United States (US) and the Dominican Republic (DR). For the past three years, our efforts have been centered on the collection of cerebrospinal fluid (CSF), plasma, serum and Paxgene tubes for RNA to study core biomarkers. Collection of blood samples for DNA to conduct genetic analyses is also ongoing.MethodThe cohort consisted of participants aged 50 and older from the DR, including those living in the New York City area, willing and able to provide a blood and CSF samples. Interviewers in the DR were trained to collect data, blood samples and CSF. DNA samples were sent overnight to Columbia university (CU) for processing. CSF, Paxgene tubes, serum and plasma samples were processed in the DR and stored at ‐80F for batch shipping to CU. APOE genotyping was conducted in the US. Biomarkers, metabolomics, and proteomics data was generated at Columbia University. Methylation assays from Paxgene was conducted at Uniformed Services University (USUHS).ResultWe have databased a total of 1899 individuals with plasma samples, 1707 with Paxgene, 1731 with serum and 203 with CSF. Blood samples from 1079 participants have genome wide arra, whole genome sequencing and APOE genotyping. 192 CSF samples have proteomics completed, 153 CSF samples have metabolomics data and 742 have plasma biomarkers (Ab40, Ab42, T‐tau, P‐tau181, NFL and GFAP)).ConclusionSample collection for genetic studies in developing countries present important logistical challenges. Despite these challenges, sample quality is comparable to those collected in New York. Biomarkers from CSF, serum and plasma can give us a closer look into underrepresented populations such as Caribbean Hispanics. Results suggest that similar protocols can be successful in Latin America. Future work will augment the biosample collection of the cohort by collecting samples from additional subjects.

Biomarker collection from the Caribbean Hispanic families from Dominican Republic and New York.

AbstractBackgroundGenetic Studies of Alzheimer’s Disease in Caribbean Hispanics (CH) has been ongoing for over 20 years. Our primary goal was to identify genes in large well‐phenotyped, multiplex families, and sporadic cases and controls. This longitudinal collection of data represents a unique resource for the scientific community. The project is led by collaborators in the United States (US) and the Dominican Republic (DR). For the past three years, our efforts have been centered on the collection of cerebrospinal fluid (CSF), plasma, serum and Paxgene tubes for RNA to study core biomarkers. Collection of blood samples for DNA to conduct genetic analyses is also ongoing.MethodThe cohort consisted of participants aged 50 and older from the DR, including those living in the New York City area, willing and able to provide a blood and CSF samples. Interviewers in the DR were trained to collect data, blood samples and CSF. DNA samples were sent overnight to Columbia university (CU) for processing. CSF, Paxgene tubes, serum and plasma samples were processed in the DR and stored at ‐80F for batch shipping to CU. APOE genotyping was conducted in the US. Biomarkers, metabolomics, and proteomics data was generated at Columbia University. Methylation assays from Paxgene was conducted at Uniformed Services University (USUHS).ResultWe have databased a total of 1899 individuals with plasma samples, 1707 with Paxgene, 1731 with serum and 203 with CSF. Blood samples from 1079 participants have genome wide arra, whole genome sequencing and APOE genotyping. 192 CSF samples have proteomics completed, 153 CSF samples have metabolomics data and 742 have plasma biomarkers (Ab40, Ab42, T‐tau, P‐tau181, NFL and GFAP)).ConclusionSample collection for genetic studies in developing countries present important logistical challenges. Despite these challenges, sample quality is comparable to those collected in New York. Biomarkers from CSF, serum and plasma can give us a closer look into underrepresented populations such as Caribbean Hispanics. Results suggest that similar protocols can be successful in Latin America. Future work will augment the biosample collection of the cohort by collecting samples from additional subjects.

Data harmonization across eight publicly available longitudinal studies of aging, neurodegeneration and dementia

AbstractBackgroundLarge‐scale multi‐study analyses are required to ensure reproducibility, reliability and generalizability in mapping neurodegeneration and risk for ADRD. However, the heterogeneity in data collection paradigms can complicate and confound data pooling; data harmonization is essential. Longitudinal studies add to the complexity of harmonization as a variety of follow‐up time points and time encoding schemes are used. Here, we pool data from 8 publicly available longitudinal neuroimaging studies on neurodegeneration and dementia to highlight differences in: 1) diagnostic categorization of controls, and people with mild cognitive impairment, and dementia; 2) the extent of follow‐up visits across neuroimaging and clinical assessments; and 3) encodings of various meta‐data elements including scanner manufacturer, sex, and handedness. To allow a systematic approach to multi‐study dementia research, we propose an initial ontological framework for longitudinal data archival and retrieval, capable of capturing similar data elements within given themes while ensuring that unique differences across studies are retained.MethodAIBL, ADNI‐1, ADNI2/GO, ADNI‐3, OASIS‐2, OASIS‐3, PREVENT‐AD, and MIRIAD, were accessed. Study designs, inclusion and exclusion criteria, and downloaded data elements were used to describe diagnostic criteria, imaging data, demographic features, and longitudinal data collection schemes. We create common terms to map data elements across studies, and a consistent naming scheme for longitudinal data.ResultFigure 1 shows the breakdown of diagnostic labels per cohort, and highlights how different cognitive labels may be assigned to people with the same performance scores, for example, on the Mini Mental State Examination (MMSE). Figure 2 highlights the differences in longitudinal data collection schemes across cohorts, and in labels of commonly collected elements. Using common terms provided an easy way to simultaneously query data across all studies, while retaining a map back to the original terms. Figure 3 showcases our proposed naming scheme for capturing longitudinal data elements using a relational ontological framework. This framework successfully harmonized data across study demographics, timepoints, and imaging properties.ConclusionMulti‐study data analyses are becoming common practice thanks to large scale efforts such as ENIGMA and GAAIN. Harmonization of meta‐data across studies will allow for efficient pooling of data for tracking disease progression and related risk over time.