Characteristics of youth with reported family history of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort

Taylor, Jerome; Asabere, Nana Yaw; Calkins, Monica E.; Moore, Tyler M.; Tang, Sunny X.; Xavier, Rose Mary; Merikangas, Alison; Wolf, Daniel H.; Almasy, Laura; Gur, Ruben C.; Gur, Raquel E.

doi:10.1016/j.schres.2019.12.021

Cited by 18 publications

(13 citation statements)

References 74 publications

(85 reference statements)

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“…94 More studies have focused on the association between adult and childhood traits, investigating similar or different symptoms across development as well as disorder trajectories (Table 2, Tables S6 and S7, available online). Associations were reported between PRSs of adult traits including schizophrenia, MDD, obsessive-compulsive disorder (OCD), anxiety, and externalizing disorder and clinical and continuous measures of the same/similar trait in childhood and adolescence 48,50,64,66,67,69−74,95−98 or in those at high risk, 99,100 although this was not always the case. 60,68,73,75,95,101−105 An exception is bipolar disorder, for which no significant associations with similar childhood traits, such as mania, were identified.…”

Section: Genetic Factors Explaining Stability In Traits or Associations With Adult Traitsmentioning

confidence: 99%

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

Akingbuwa

Hammerschlag

Bartels

et al. 2022

Journal of the American Academy of Child & Adolescent Psych

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Objective: A systematic review of studies using molecular genetics and statistical approaches to investigate the role of common genetic variation in the development, persistence, and comorbidity of childhood psychiatric traits was conducted. Method: A literature review was performed using the PubMed database, following the Preferred Reporting Items for Meta-Analyses guidelines. There were 131 studies meeting inclusion criteria, having investigated at least one type of childhood-onset or childhood-measured psychiatric disorder or trait with the aim of identifying trait-associated common genetic variants, estimating the contribution of single nucleotide polymorphisms to the amount of variance explained (single nucleotide polymorphism heritability), investigating genetic overlap between psychiatric traits, or investigating whether the stability in traits or the association with adult traits is explained by genetic factors. Results: The first robustly associated genetic variants have started to be identified for childhood psychiatric traits. There were substantial contributions of common genetic variants to many traits, with variation in single nucleotide polymorphism heritability estimates depending on age and raters. Moreover, genetic variants also appeared to explain comorbidity as well as stability across a range of psychiatric traits in childhood and across the life span. Conclusion: Common genetic variation plays a substantial role in childhood psychiatric traits. Increased sample sizes will lead to increased power to identify genetic variants and to understand genetic architecture, which will ultimately be beneficial to targeted and prevention strategies. This can be achieved by harmonizing phenotype measurements, as is already proposed by large international consortia and by including the collection of genetic material in every study.

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Section: Genetic Factors Explaining Stability In Traits or Associations With Adult Traitsmentioning

confidence: 99%

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

Akingbuwa

Hammerschlag

Bartels

et al. 2022

Journal of the American Academy of Child & Adolescent Psych

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“…A variety of NLP techniques have been used to characterize different language phenotypes in psychosis with varying degrees of success, mostly focusing on SSD 8 . Here, “schizophrenia spectrum disorders” (SSD) refers to threshold-level primary psychotic disorders 9 , 10 . Elvevåg et al 11 first applied Latent Semantic Analysis to quantify decreased coherence in SSD speech and was able to predict human ratings of organizational structure, tangentiality, and content, as well as discriminating between SSD and control participants with 80–82% accuracy.…”

Section: Introductionmentioning

confidence: 99%

Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders

et al. 2021

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Computerized natural language processing (NLP) allows for objective and sensitive detection of speech disturbance, a hallmark of schizophrenia spectrum disorders (SSD). We explored several methods for characterizing speech changes in SSD (n = 20) compared to healthy control (HC) participants (n = 11) and approached linguistic phenotyping on three levels: individual words, parts-of-speech (POS), and sentence-level coherence. NLP features were compared with a clinical gold standard, the Scale for the Assessment of Thought, Language and Communication (TLC). We utilized Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art embedding algorithm incorporating bidirectional context. Through the POS approach, we found that SSD used more pronouns but fewer adverbs, adjectives, and determiners (e.g., “the,” “a,”). Analysis of individual word usage was notable for more frequent use of first-person singular pronouns among individuals with SSD and first-person plural pronouns among HC. There was a striking increase in incomplete words among SSD. Sentence-level analysis using BERT reflected increased tangentiality among SSD with greater sentence embedding distances. The SSD sample had low speech disturbance on average and there was no difference in group means for TLC scores. However, NLP measures of language disturbance appear to be sensitive to these subclinical differences and showed greater ability to discriminate between HC and SSD than a model based on clinical ratings alone. These intriguing exploratory results from a small sample prompt further inquiry into NLP methods for characterizing language disturbance in SSD and suggest that NLP measures may yield clinically relevant and informative biomarkers.

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“…Our findings provide evidence that familial loading for psychosis, most likely reflecting an increased genetic predisposition [61,62], individually or jointly with an environmental component such as parental socioeconomic background may moderate premorbid functioning among individuals who will later develop a psychotic disorder. Family-based studies have previously reported adjustment difficulties in relatives of psychotic patients, suggesting the involvement of presumed genetic influences [6,18,34,36].…”

Section: Discussionmentioning

confidence: 71%

“…Cases reporting that a first or second degree relative was diagnosed with affective or nonaffective psychotic disorder were marked as having positive FHP (details in supplementary text). Positive FHP has been considered a proxy phenotype for increased genetic risk of psychosis [46,47], supported by molecular genetic evidence demonstrating that individuals with positive FHP are characterized by higher polygenic loading for SZ [61,62].…”

Section: Family Historymentioning

confidence: 99%

Familial and socioeconomic contributions to premorbid functioning in psychosis: Impact on age at onset and treatment response

et al. 2020

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Background. Premorbid adjustment (PA) abnormalities in psychotic disorders are associated with an earlier age at onset (AAO) and unfavorable clinical outcomes, including treatment resistance. Prior family studies suggest that familial liability, likely reflecting increased genetic risk, and socioeconomic status (SES) contribute to premorbid maladjustment. However, their joint effect possibly indicating gene–environment interaction has not been evaluated. Methods. We examined whether family history of psychosis (FHP) and parental SES may predict PA and AAO in unrelated cases with first-episode psychosis (n = 108) and schizophrenia (n = 104). Premorbid academic and social functioning domains during childhood and early adolescence were retrospectively assessed. Regression analyses were performed to investigate main effects of FHP and parental SES, as well as their interaction. The relationships between PA, AAO, and response to antipsychotic medication were also explored. Results. Positive FHP associated with academic PA difficulties and importantly interacted with parental SES to moderate social PA during childhood (interaction p = 0.024). Positive FHP and parental SES did not predict differences in AAO. Nevertheless, an earlier AAO was observed among cases with worse social PA in childhood (β = −0.20; p = 0.005) and early adolescence (β = −0.19; p = 0.007). Further, confirming evidence emerged for an association between deficient childhood social PA and poor treatment response (p = 0.04). Conclusions. Familial risk for psychosis may interact with parental socioeconomic position influencing social PA in childhood. In addition, this study supports the link between social PA deviations, early psychosis onset, and treatment resistance, which highlights premorbid social functioning as a promising clinical indicator.

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Characteristics of youth with reported family history of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort

Cited by 18 publications

References 74 publications

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders

Familial and socioeconomic contributions to premorbid functioning in psychosis: Impact on age at onset and treatment response

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