Publications by authors named "Nelson Freimer"

Digital sensing tools, like smartphones and wearables, offer transformative potential for mental health research by enabling scalable, longitudinal data collection. Realizing this promise requires overcoming significant challenges including limited data standards, underpowered studies, and a disconnect between research aims and community needs. This report, based on the 2023 Workshop on Advancing Digital Sensing Tools for Mental Health, articulates strategies to address these challenges to ensure rigorous, equitable, and impactful research.

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Objectives: Most bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia.

Methods: We employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD.

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Experimental cognitive tests are designed to measure particular cognitive domains, although evidence supporting test validity is often limited. The Consortium for Neuropsychiatric Phenomics test battery administered 23 experimental and traditional neuropsychological tests to a large sample of community volunteers ( = 1,059) and patients with psychiatric diagnoses ( = 137), providing a unique opportunity to examine convergent validity with factor analysis. Traditional tests included subtests from the Wechsler and Delis-Kaplan batteries, while experimental tests included the Attention Networks Test, Balloon Analogue Risk Task, Delay Discounting Task, Remember-Know, Reversal Learning Task, Scene Recognition, Spatial and Verbal Capacity and Manipulation Tasks, Stop-Signal Task, and Task Switching.

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Article Synopsis
  • - The PUMAS project aims to address the lack of representation of African and Latin American populations in psychiatric genetics studies by analyzing genetic data from individuals with serious mental illness (SMI), including disorders like schizophrenia and bipolar disorder, using data from 89,320 participants across four different cohorts.
  • - The research involves harmonizing data from various clinical assessments to create standardized measures of mental health symptoms, which allows for more accurate genetic analyses across different diagnoses and symptoms.
  • - The findings show that schizophrenia and severe bipolar disorder are the most common diagnoses among participants, and a set of 19 key symptoms has been identified, which may be useful for cross-diagnosis genetic studies.
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We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations.

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Perinatal depression (PND) affects up to 20% of women and is associated with significant impairment and disability in affected women. In addition, perinatal depression is associated with broader public health and multigenerational consequences. Innovative approaches are needed to reduce the burden of perinatal depression through identification, tracking, and treatment of depressive symptoms during the perinatal period.

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Article Synopsis
  • Significant advancements have been made in using data from smartphones and wearables to track depressive moods over the past decade, but many studies struggle with replicability and validity of depression measures.
  • This study involved 183 individuals and combined adaptive testing with continuous behavioral data over 40 weeks, achieving high prediction accuracy of future mood based on digital data.
  • The findings demonstrate the potential for more personalized behavioral assessments in mental health research, allowing for predictions of symptom severity weeks ahead.
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Background: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas.

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Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD.

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Background: The global burden of anxiety and depression has created an urgent need for scalable approaches to increase access to evidence-based mental health care. The Screening and Treatment for Anxiety and Depression (STAND) system of care was developed to meet this need through the use of internet-connected devices for assessment and provision of treatment. STAND triages to level of care (monitoring only, digital therapy with coaches, digital therapy assisted by clinicians in training, and clinical care) and then continuously monitors symptoms to adapt level of care.

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Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries.

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In the last 300 thousand years, the genus expanded from equatorial Africa into the southernmost latitudes of the continent, where colder climate was a probable driver of natural selection. We investigated population-level genetic variation in the mitochondrial uncoupling protein 1 () gene region-implicated in non-shivering thermogenesis (NST)-in 73 wild savannah monkeys from three taxa representing this southern expansion ( and ) ranging from Kenya to South Africa. We found 17 single nucleotide polymorphisms with extended haplotype homozygosity consistent with positive selective sweeps, 10 of which show no significant linkage disequilibrium with each other.

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Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study.

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Background: Educational attainment is associated with wellbeing and health, but patients with schizophrenia achieve lower levels of education than people without. Several effective interventions can ameliorate this situation. However, the magnitude of the education gap in schizophrenia and its change over time are unclear.

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Recruiting, training and retaining scientists in computational biology is necessary to develop a workforce that can lead the quantitative biology revolution. Yet, African-American/Black, Hispanic/Latinx, Native Americans, and women are severely underrepresented in computational biosciences. We established the UCLA Bruins-in-Genomics Summer Research Program to provide training and research experiences in quantitative biology and bioinformatics to undergraduate students with an emphasis on students from backgrounds underrepresented in computational biology.

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We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8.

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Article Synopsis
  • * Researchers discovered 287 genomic regions associated with schizophrenia, emphasizing genes specifically active in excitatory and inhibitory neurons, and identified 120 key genes potentially responsible for these associations.
  • * The findings highlight important biological processes related to neuronal function, suggesting overlaps between common and rare genetic variants in both schizophrenia and neurodevelopmental disorders, ultimately aiding future research on these conditions.
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Article Synopsis
  • A meta-analysis of whole exomes from 24,248 schizophrenia cases and 97,322 controls identified ultra-rare coding variants (URVs) linked to schizophrenia risk across 10 significant genes.
  • Some of these genes are heavily expressed in the brain and are involved in synapse formation, pointing to a connection between glutamate system dysfunction and schizophrenia.
  • Additionally, there's an overlap in rare variant risks shared with other disorders like autism and epilepsy, suggesting that both common and rare genetic factors contribute to the same biological processes underlying schizophrenia.
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Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland.

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  • The study investigates the genetic and phenotypic traits associated with age at onset (AAO) and polarity at onset (PAO) in bipolar disorder to enhance understanding of the illness and develop screening tools.
  • Results indicate that an earlier AAO is linked to more severe symptoms, such as psychosis and suicidality, as well as variations in educational success and living situations.
  • The research reveals a significant relationship between higher polygenic risk scores for other mental disorders and earlier AAO, although no significant associations were found for PAO, highlighting considerable variability across different cohorts.
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DNA methylation-based biomarkers of aging have been developed for many mammals but not yet for the vervet monkey (Chlorocebus sabaeus), which is a valuable non-human primate model for biomedical studies. We generated novel DNA methylation data from vervet cerebral cortex, blood, and liver using highly conserved mammalian CpGs represented on a custom array (HorvathMammalMethylChip40). We present six DNA methylation-based estimators of age: vervet multi-tissue epigenetic clock and tissue-specific clocks for brain cortex, blood, and liver.

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University campuses could become leaders in developing alternatives to policing for managing public health and safety, yet, nearly all campuses rely on campus or local police to respond to mental health emergencies. Herein, we present the available evidence for campus mobile crisis intervention teams (MCITs) as an alternative to policing, consider what colleges and universities can learn from existing community MCIT models, and propose initial steps for the development and implementation of a campus MCIT.

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Background: Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718).

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Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets.

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Article Synopsis
  • Bipolar disorder has a genetic basis and complex causes; a large study compared nearly 42,000 bipolar patients with over 371,000 healthy controls, revealing 64 genomic regions linked to the disorder.
  • The findings showed that risk-related genes are heavily associated with brain functions, particularly in areas like the prefrontal cortex and hippocampus, and they include targets for various medications.
  • The research also distinguished between bipolar disorder types I and II, revealing a close genetic relationship and highlighting 15 specific genes that could lead to new treatment options and further investigations.
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