Publications by authors named "Douglas Levinson"

Article Synopsis
  • - The study aimed to explore the genetic basis of major depressive disorder by analyzing symptoms across various clinical and community cohorts, acknowledging challenges like sample size differences and missing data patterns.
  • - Researchers performed genome-wide association studies using data from both diagnosed and undiagnosed participants, fitting models to understand the relationships between different depressive symptoms.
  • - Findings emphasized the relevance of symptom directionality (e.g., hypersomnia vs. insomnia) and the necessity of considering study design when analyzing genetic data related to depression.
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  • Accurately diagnosing bipolar disorder (BD) can take around 7 years due to its overlap with unipolar major depressive disorder (MDD), especially since the first manic episode often follows a depressive one.
  • This study uses genome-wide association analyses (GWAS) and polygenic risk scores (PRS) from a large cohort to identify genetic factors that could help differentiate between BD and MDD early on.
  • The results show that while BD and MDD are genetically distinct and share a continuum of genetic risk, larger future studies are needed to enhance the accuracy of these genetic predictors for early diagnosis.
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Background: Previous pandemics have had negative effects on mental health, but there are few data on children and adolescents who were receiving ongoing psychiatric treatment.

Aims: To study changes in emotions and clinical state, and their predictors, during the COVID-19 pandemic in France.

Method: We administered (by interview) the baseline Youth Self-Report version of the CoRonavIruS Health Impact Survey v0.

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Article Synopsis
  • Major depressive disorder shows varied symptoms, and genetic analysis can help identify specific subtypes and clinical profiles.
  • Challenges in integrating symptom data arise from differences in sample sizes and patterns of missing data in clinical vs. community groups.
  • The study used genome-wide association studies to find that a model including unique symptom factors and accounting for missing data best represented the symptoms of depression, highlighting the need to consider symptom directionality and study design when analyzing genetic data.
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Pediatric acute-onset neuropsychiatric syndrome (PANS) is an abrupt-onset neuropsychiatric disorder. PANS patients have an increased prevalence of comorbid autoimmune illness, most commonly arthritis. In addition, an estimated one-third of PANS patients present with low serum C4 protein, suggesting decreased production or increased consumption of C4 protein.

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Excess synaptic pruning during neurodevelopment has emerged as one of the leading hypotheses on the causal mechanism for schizophrenia. It proposes that excess synaptic elimination occurs during development before the formal onset of illness. Accordingly, synaptic deficits may be observable at all stages of illnesses, including in the early phases.

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Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes. This recent study-and most other large-scale human genetics studies-was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear.

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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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This study investigates if genetic factors could contribute to the high rate of mood disorders reported in a U.S. community known to have a restricted early founder population (confirmed here through runs of homozygosity analysis).

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Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing 'depression-like' shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.

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Structural variation in the complement 4 gene (C4) confers genetic risk for schizophrenia. The variation includes numbers of the increased C4A copy number, which predicts increased C4A mRNA expression. C4-anaphylatoxin (C4-ana) is a C4 protein fragment released upon C4 protein activation that has the potential to change the blood-brain barrier (BBB).

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Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

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Heterozygous deletions constitute the most prevalent currently known single-gene mutation associated with schizophrenia, and additionally predispose to multiple other neurodevelopmental disorders. Engineered heterozygous deletions impaired neurotransmitter release in human neurons, suggesting a synaptic pathophysiological mechanism. Utilizing this observation for drug discovery, however, requires confidence in its robustness and validity.

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  • - The study reviews the link between narcolepsy, a rare sleep disorder, and psychosis in both children and adults, highlighting diagnostic and therapeutic challenges related to their relationship.
  • - Researchers identified three groups: typical narcoleptics with mild hallucinations, atypical narcoleptics with severe hallucinations and delusions, and those with comorbid schizophrenia who exhibit psychotic symptoms independent of sleep.
  • - Findings suggest that psychostimulants for narcolepsy can exacerbate psychotic symptoms, and there may be a potential relationship between early-onset narcolepsy and schizophrenia due to overlapping neurodevelopmental factors, leading to the proposal of a clinical management algorithm.
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ABO blood types and their corresponding antigens have long been assumed to be related to different human diseases. So far, smaller studies on the relationship between mental disorders and blood types yielded contradicting results. In this study we analyzed the association between ABO blood types and lifetime major depressive disorder (MDD).

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  • Smoking rates are significantly higher among individuals with schizophrenia, with over 60% of this population being regular tobacco users, compared to 17% of the general US adult population.
  • Research suggests a genetic link between smoking and schizophrenia, but few studies have looked at specific genetic variants impacting smoking behaviors in people with schizophrenia.
  • Findings from a large genetic study indicate significant correlations between schizophrenia and various smoking behaviors, and a new genetic association related to smoking frequency was identified, highlighting shared genetic factors for both conditions.
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Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions presents a difficult signal-to-noise problem. Using a machine-learning method (RetroSom) and deep whole-genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains.

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Purpose: Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of individuals who have been diagnosed with depression at some point in their lifetime. The purpose of establishing this cohort is to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants.

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Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD.

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Psychotic disorders in children are more heterogeneous than is captured by categorical diagnoses. In a new cohort of children and adolescents, we evaluated the relationships among age at onset (AAO), clinical symptoms and developmental impairments. Patients with schizophrenia and other "spectrum" psychotic diagnoses (N = 88; AAO 6-17, mean 12.

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Background: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.

Methods: We fine-mapped the classical MHC (chr6: 29.

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