Publications by authors named "Justin Tubbs"

Schizophrenia (SCZ) is a complex psychiatric disorder presenting challenges for characterization. The current study aimed to identify and evaluate disease-responsive essential genes (DREGs) to enhance the molecular characterization of SCZ. RNA-sequencing data from PsychENCODE (536 SCZ patients, 832 controls) and peripheral blood transcriptome data from 144 recruited subjects (59 SCZ patients, 6 non-SCZ psychiatric patients, 79 controls) are analyzed.

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Objective: Antidepressants are commonly prescribed medications in the United States, however, factors underlying response are poorly understood. Electronic health records (EHRs) provide a cost-effective way to create and test response algorithms on large, longitudinal cohorts. We describe a new antidepressant response algorithm, validation in two independent EHR databases, and genetic associations with antidepressant response.

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Article Synopsis
  • Major depressive disorder (MDD) is a common illness that causes difficulties in life, and scientists are studying how genetics and environment influence it.
  • This study looked at 10,032 people in Nepal to understand the genetic factors related to MDD and found that both genetics and a person's life experiences matter.
  • Although the genetic factors for MDD in Nepal were similar to those found in European studies, the methods used for predicting MDD based on European data did not work well for Nepalese people, suggesting more research is needed.
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Polygenic risk scores (PRSs) are promising tools for advancing precision medicine. However, existing PRS construction methods rely on static summary statistics derived from genome-wide association studies (GWASs), which are often updated at lengthy intervals. As genetic data and health outcomes are continuously being generated at an ever-increasing pace, the current PRS training and deployment paradigm is suboptimal in maximizing the prediction accuracy of PRSs for incoming patients in healthcare settings.

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Rare and low-frequency variants contribute to schizophrenia (SCZ), and may influence its age-at-onset (AAO). We examined the association of rare or low-frequency deleterious coding variants in Chinese patients with SCZ. We collected DNA samples in 197 patients with SCZ spectrum disorder and 82 healthy controls (HC), and performed exome sequencing.

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Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR.

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A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 205 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls.

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Article Synopsis
  • Research shows a link between schizophrenia and white blood cell counts (WBC), but it's complicated by factors like antipsychotic medication.
  • A two-sample Mendelian randomization (MR) was conducted using large data sets to understand genetic relationships between schizophrenia and lymphocyte counts.
  • Results indicated a bidirectional genetic relationship between lymphocyte count and schizophrenia, while findings regarding eosinophil count were less clear, highlighting the complex connections at play.
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Background: Rare variants are likely to contribute to schizophrenia (SCZ), given the large discrepancy between the heritability estimated from twin and GWAS studies. Furthermore, the nature of the rare-variant contribution to SCZ may vary with the "age-at-onset" (AAO), since early-onset has been suggested as being indicative of neurodevelopment deviance.

Objective: To examine the association of rare deleterious coding variants in early- and adult-onset SCZ in a Chinese sample.

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Psychotic disorders are debilitating conditions with disproportionately high public health burden. Genetic studies indicate high heritability, but current polygenic scores (PGS) account for only a fraction of variance in psychosis risk. PGS often show poor portability across ancestries, performing significantly worse in non-European populations.

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A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 206 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls.

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Importance: Modeling genetic nurture (ie, the effects of parental genotypes through influences on the environment experienced by their children) is essential to accurately disentangle genetic and environmental influences on phenotypic variance. However, these influences are often ignored in both epidemiologic and genetic studies of depression.

Objective: To estimate the association of genetic nurture with depression and neuroticism.

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Mendelian randomization using GWAS summary statistics has become a popular method to infer causal relationships across complex diseases. However, the widespread pleiotropy observed in GWAS has made the selection of valid instrumental variables problematic, leading to possible violations of Mendelian randomization assumptions and thus potentially invalid inferences concerning causation. Furthermore, current MR methods can examine causation in only one direction, so that two separate analyses are required for bi-directional analysis.

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Article Synopsis
  • Schizophrenia (SCZ) is a complex mental health disorder influenced by genetic factors, with studies revealing a gap in understanding due to undetected medium-sized structural variants (SVs).
  • The research aimed to identify these SVs in families with chronic SCZ characterized by severe negative symptoms and cognitive deficits.
  • By using advanced third-generation sequencing techniques, the study discovered 88 SVs associated with 79 genes, linking them to important brain functions and development pathways, which could help explain some aspects of the heritability of SCZ.
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Human neuropsychiatric disorders are associated with genetic and environmental factors affecting the brain, which has been subjected to strong evolutionary pressures resulting in an enlarged cerebral cortex and improved cognitive performance. Thus, genes involved in human brain evolution may also play a role in neuropsychiatric disorders. We test whether genes associated with 7 neuropsychiatric phenotypes are enriched in genomic regions that have experienced rapid changes in human evolution (HARs) and importantly, whether HAR status interacts with developmental brain expression to predict associated genes.

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Nonparametric maximum likelihood estimation encompasses a group of classic methods to estimate distribution-associated functions from potentially censored and truncated data, with extensive applications in survival analysis. These methods, including the Kaplan-Meier estimator and Turnbull's method, often result in overfitting, especially when the sample size is small. We propose an improvement to these methods by applying kernel smoothing to their raw estimates, based on a BIC-type loss function that balances the trade-off between optimizing model fit and controlling model complexity.

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Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging.

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The sensation of pressure allows us to feel sustained compression and body strain. While our understanding of cutaneous touch has grown significantly in recent years, how deep tissue sensations are detected remains less clear. Here, we use quantitative sensory evaluations of patients with rare sensory disorders, as well as nerve blocks in typical individuals, to probe the neural and genetic mechanisms for detecting non-painful pressure.

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Disaggregation and estimation of genetic effects from offspring and parents has long been of interest to statistical geneticists. Recently, technical and methodological advances have made the genome-wide and loci-specific estimation of direct offspring and parental genetic nurture effects more possible. However, unbiased estimation using these methods requires datasets where both parents and at least one child have been genotyped, which are relatively scarce.

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Schizophrenia is a severe neuropsychiatric disorder with core features including hallucinations, delusions, and cognition deficits. Accumulating evidence has implicated abnormal DNA methylation in the development of schizophrenia. However, the mechanisms by which DNA methylation changes alter the risk for schizophrenia remain largely unknown.

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Article Synopsis
  • Indirect parental genetic effects refer to how a parent's genes influence their child's traits beyond just the genes passed down directly.
  • The study showcases a method to estimate these genetic effects at individual genetic locations using large genome-wide association study (GWAS) data, even when parental genotypes are not available.
  • They developed a software tool called IMPISH, which helps researchers quickly estimate parental genotypes from related individuals and apply this data in genetic analyses.
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Depression is the world's leading cause of disability. Greater understanding of the neurobiological basis of depression is necessary for developing novel treatments with improved efficacy and acceptance. Recently, major advances have been made in the search for genetic variants associated with depression which may help to elucidate etiological mechanisms.

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Neuroscientific research on pleasant touch has focused on the C-tactile pathway for gentle stroking and has successfully explained how these sensory fibers transmit information about affective social touch to the brain and induce sensations of pleasantness. The C-tactile social/affective touch hypothesis even proposes that C-tactile fibers form a privileged pathway underlying social touch. However, deep pressure is a type of touch commonly considered pleasant and calming, occurring in hugs, cuddling, and massage.

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Recently, methods have been introduced using polygenic scores (PGS) to estimate the effects of genetic nurture, the environmentally-mediated effects of parental genotypes on the phenotype of their child above and beyond the effects of the alleles which are transmitted to the child. We introduce a simplified model for estimating genetic nurture effects and show, through simulation and analytical derivation, that our method provides unbiased estimates and offers an increase in power to detect genetic nurture of up to 1/3 greater than that of previous methods. Subsequently, we apply this method to data from the Avon Longitudinal Study of Parents and Children to estimate the effects of maternal genetic nurture on childhood body mass index (BMI) trajectories.

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