Requirements and operational guidelines for secure and sustainable digital phenotyping:Design and development study

Background: Digital phenotyping, the measurement of human behavioral phenotypes using personal devices, is rapidly gaining popularity. Novel initiatives, ranging from software prototypes to user-ready research platforms, are innovating the field of biomedical research and health care apps. One example is the BEHAPP project, which offers a fully managed digital phenotyping platform as a service. The innovative potential of digital phenotyping strategies resides among others in their capacity to objectively capture measurable and quantitative components of human behavior, such as diurnal rhythm, movement patterns, and communication, in a real-world setting. The rapid development of this field underscores the importance of reliability and safety of the platforms on which these novel tools are operated. Large-scale studies and regulated research spaces (eg, the pharmaceutical industry) have strict requirements for the software-based solutions they use. Security and sustainability are key to ensuring continuity and trust. However, the majority of behavioral monitoring initiatives have not originated primarily in these regulated research spaces, which may be why these components have been somewhat overlooked, impeding the further development and implementation of such platforms in a secure and sustainable way.Objective: This study aims to provide a primer on the requirements and operational guidelines for the development and operation of a secure behavioral monitoring platform.Methods: We draw from disciplines such as privacy law, information, and computer science to identify a set of requirements and operational guidelines focused on security and sustainability. Taken together, the requirements and guidelines form the foundation of the design and implementation of the BEHAPP behavioral monitoring platform.Results: We present the base BEHAPP data collection and analysis flow and explain how the various concepts from security and sustainability are addressed in the design.Conclusions: Digital phenotyping initiatives are steadily maturing. This study helps the field and surrounding stakeholders to reflect upon and progress toward secure and sustainable operation of digital phenotyping–driven research

Social behavior assessment in cognitively impaired older adults using a passive and remote smartphone application

BACKGROUND: In Alzheimer's Disease (AD), loss of social interactions has a major impact on well-being. Therefore, AD patients would benefit from early detection of symptoms of social withdrawal. Current measurement techniques such as questionnaires are subjective and rely on recall, in contradiction to smartphone applications, which measure social behavior passively and objectively. Here, we examine social interactions through passive remote monitoring with the smartphone application BEHAPP in cognitively impaired participants. This study aims to investigate (1) the association between demographic characteristics and BEHAPP outcome variables in cognitively normal (CN) older adults, (2) if social behavior as measured using the passive smartphone app BEHAPP is impaired in cognitively impaired (CI) participants compared to subjects with subjective cognitive decline (SCD), and CN older adults. In addition, we explored in a subset of individuals the association between BEHAPP outcomes and neuropsychiatric symptoms. METHOD: CN (n=209), SCD (n=55) and CI (n=22) participants, older than 45 years, installed the BEHAPP app on their own Android smartphone for 7-42 days. CI participants had a clinical diagnosis of mild cognitive impairment or AD-type dementia. The app continuously measured communication events, application usage and location. Neuropsychiatric Inventory (NPI) total scores were available from 20 SCD and 22 CI participants. RESULT: We found that older cognitively healthy participants called less frequently and made less use of apps. No sex effects were found. Linear models corrected for age, sex and education showed that compared to the CN and SCD groups, CI participants called less unique contacts and contacted the same contacts relatively more often (Figure 1). They also made less use of apps, visited less unique places and traveled less far from home. Higher total NPI scores were associated with more unique stay points and further travelling. Similar behavior patterns were found when correcting for multiple comparisons. CONCLUSION: Cognitively impaired individuals show reduced social activity, as measured by the smartphone application BEHAPP. Neuropsychiatric symptoms seemed only marginally associated with social behavior as measured with BEHAPP. This research shows that a passive and remote smartphone application is able to objectively and passively measure altered social behavior in a cognitively impaired population

22q11.2 deletion syndrome

22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal microdeletion disorder, estimated to result mainly from de novo non-homologous meiotic recombination events occurring in approximately 1 in every 1,000 fetuses. The first description in the English language of the constellation of findings now known to be due to this chromosomal difference was made in the 1960s in children with DiGeorge syndrome, who presented with the clinical triad of immunodeficiency, hypoparathyroidism and congenital heart disease. The syndrome is now known to have a heterogeneous presentation that includes multiple additional congenital anomalies and later-onset conditions, such as palatal, gastrointestinal and renal abnormalities, autoimmune disease, variable cognitive delays, behavioural phenotypes and psychiatric illness - all far extending the original description of DiGeorge syndrome. Management requires a multidisciplinary approach involving paediatrics, general medicine, surgery, psychiatry, psychology, interventional therapies (physical, occupational, speech, language and behavioural) and genetic counselling. Although common, lack of recognition of the condition and/or lack of familiarity with genetic testing methods, together with the wide variability of clinical presentation, delays diagnosis. Early diagnosis, preferably prenatally or neonatally, could improve outcomes, thus stressing the importance of universal screening. Equally important, 22q11.2DS has become a model for understanding rare and frequent congenital anomalies, medical conditions, psychiatric and developmental disorders, and may provide a platform to better understand these disorders while affording opportunities for translational strategies across the lifespan for both patients with 22q11.2DS and those with these associated features in the general population

Proline and COMT Status Affect Visual Connectivity in Children with 22q11.2 Deletion Syndrome

Background Individuals with the 22q11.2 deletion syndrome (22q11DS) are at increased risk for schizophrenia and Autism Spectrum Disorders (ASDs). Given the prevalence of visual processing deficits in these three disorders, a causal relationship between genes in the deleted region of chromosome 22 and visual processing is likely. Therefore, 22q11DS may represent a unique model to understand the neurobiology of visual processing deficits related with ASD and psychosis. Methodology We measured Event-Related Potentials (ERPs) during a texture segregation task in 58 children with 22q11DS and 100 age-matched controls. The C1 component was used to index afferent activity of visual cortex area V1; the texture negativity wave provided a measure for the integrity of recurrent connections in the visual cortical system. COMT genotype and plasma proline levels were assessed in 22q11DS individuals. Principal Findings Children with 22q11DS showed enhanced feedforward activity starting from 70 ms after visual presentation. ERP activity related to visual feedback activity was reduced in the 22q11DS group, which was seen as less texture negativity around 150 ms post presentation. Within the 22q11DS group we further demonstrated an association between high plasma proline levels and aberrant feedback/feedforward ratios, which was moderated by the COMT158 genotype. Conclusions These findings confirm the presence of early visual processing deficits in 22q11DS. We discuss these in terms of dysfunctional synaptic plasticity in early visual processing areas, possibly associated with deviant dopaminergic and glutamatergic transmission. As such, our findings may serve as a promising biomarker related to the development of schizophrenia among 22q11DS individuals

Investigation of the genetic association between quantitative measures of psychosis and schizophrenia:A polygenic risk score analysis

The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom scores were available. The genetic risk score of schizophrenia was significantly associated with case-control status (p<0.0001). In the case-control sample, the five psychosis dimensions were found to be significantly associated with genetic risk scores; the correlations ranged between.15 and.27 (all p<.001). However, these correlations were not significant in schizophrenia cases or controls separately. While this study confirms the presence of a genetic risk for schizophrenia as categorical diagnostic trait, we did not find evidence for the genetic risk underlying quantitative schizophrenia symptom dimensions. This does not necessarily imply that a genetic basis is nonexistent, but does suggest that it is distinct from the polygenic risk score for schizophrenia

A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data

The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliably preprocesses raw smartphone-based location data in such a manner that relevant behavioral phenotypes of interest can be derived

Effect of disease related biases on the subjective assessment of social functioning in Alzheimer's disease and schizophrenia patients

Background: Questionnaires are the current hallmark for quantifying social functioning in human clinical research. In this study, we compared self- and proxy-rated (caregiver and researcher) assessments of social functioning in Schizophrenia (SZ) and Alzheimer's disease (AD) patients and evaluated if the discrepancy between the two assessments is mediated by disease-related factors such as symptom severity. Methods: We selected five items from the WHO Disability Assessment Schedule 2.0 (WHODAS) to assess social functioning in 53 AD and 61 SZ patients. Caregiver- and researcher-rated assessments of social functioning were used to calculate the discrepancies between self-rated and proxy-rated assessments. Furthermore, we used the number of communication events via smartphones to compare the questionnaire outcomes with an objective measure of social behaviour. Results: WHODAS results revealed that both AD (p &lt; 0.001) and SZ (p &lt; 0.004) patients significantly overestimate their social functioning relative to the assessment of their caregivers and/or researchers. This overestimation is mediated by the severity of cognitive impairments (MMSE; p = 0.019) in AD, and negative symptoms (PANSS; p = 0.028) in SZ. Subsequently, we showed that the proxy scores correlated more strongly with the smartphone communication events of the patient when compared to the patient-rated questionnaire scores (self; p = 0.076, caregiver; p &lt; 0.001, researcher-rated; p = 0.046). Conclusion: Here we show that the observed overestimation of WHODAS social functioning scores in AD and SZ patients is partly driven by disease-related biases such as cognitive impairments and negative symptoms, respectively. Therefore, we postulate the development and implementation of objective measures of social functioning that may be less susceptible to such biases.The PRISM project (www.prism-project.eu) leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115916. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This publication reflects only the authors’ views neither IMI JU nor EFPIA nor the European Commission are liable for any use that may be made of the information contained therein. Dr. Arango has also received funding support by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds. Fundación Familia Alonso and Fundación Alicia Koplowit

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm&lt; 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Social responsiveness scale-aided analysis of the clinical impact of copy number variations in autism

Recent array-based studies have detected a wealth of copy number variations (CNVs) in patients with autism spectrum disorders (ASD). Since CNVs also occur in healthy individuals, their contributions to the patient’s phenotype remain largely unclear. In a cohort of children with symptoms of ASD, diagnosis of the index patient using ADOS-G and ADI-R was performed, and the Social Responsiveness Scale (SRS) was administered to the index patients, both parents, and all available siblings. CNVs were identified using SNP arrays and confirmed by FISH or array CGH. To evaluate the clinical significance of CNVs, we analyzed three families with multiple affected children (multiplex) and six families with a single affected child (simplex) in which at least one child carried a CNV with a brain-transcribed gene. CNVs containing genes that participate in pathways previously implicated in ASD, such as the phosphoinositol signaling pathway (PIK3CA, GIRDIN), contactin-based networks of cell communication (CNTN6), and microcephalin (MCPH1) were found not to co-segregate with ASD phenotypes. In one family, a loss of CNTN5 co-segregated with disease. This indicates that most CNVs may by themselves not be sufficient to cause ASD, but still may contribute to the phenotype by additive or epistatic interactions with inherited (transmitted) mutations or non-genetic factors. Our study extends the scope of genome-wide CNV profiling beyond de novo CNVs in sporadic patients and may aid in uncovering missing heritability in genome-wide screening studies of complex psychiatric disorders