Evidence of Slow Neural Processing, Developmental Differences and Sensitivity to Cannabis Effects in a Sample at Clinical High Risk for Psychosis From the NAPLS Consortium Assessed With the Human Startle Paradigm

Cadenhead, Kristin S.; Duncan, Erica; Addington, Jean; Bearden, Carrie E.; Cannon, Tyrone D.; Cornblatt, Barbara A.; Mathalon, Daniel H.; McGlashan, Thomas H.; Perkins, Diana O.; Seidman, Larry J.; Tsuang, Ming T.; Walker, Elaine F.; Woods, Scott W.; Bauchman, Peter; Belger, A.; Carrión, Ricardo; Donkers, Franc C. L.; Johannesen, Jason; Light, Gregory A.; Niznikiewicz, Margaret; Nunag, Jason; Roach, Brian

doi:10.3389/fpsyt.2020.00833

Cited by 4 publications

(3 citation statements)

References 60 publications

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“…There are a small number of studies that found no difference between SCZ and CON subjects (24,(31)(32)(33). Slower latency at baseline predicted which adolescent and young adult subjects at high risk for developing SCZ went on to convert to psychosis over a 2-years period in a multisite study of prodromal SCZ (34). Importantly for the current paper, latency was slower in TOXO seropositive than seronegative subjects, and this finding was evident both in SCZ and CON subjects in the cohort (35).…”

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Toxoplasma gondii Effects on the Relationship of Kynurenine Pathway Metabolites to Acoustic Startle Latency in Schizophrenia vs. Control Subjects

et al. 2020

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Background: Chronic infection with Toxoplasma gondii (TOXO) results in microcysts in the brain that are controlled by inflammatory activation and subsequent changes in the kynurenine pathway. TOXO seropositivity is associated with a heightened risk of schizophrenia (SCZ) and with cognitive impairments. Latency of the acoustic startle response, a putative index of neural processing speed, is slower in SCZ. SCZ subjects who are TOXO seropositive have slower latency than SCZ subjects who are TOXO seronegative. We assessed the relationship between kynurenine pathway metabolites and startle latency as a potential route by which chronic TOXO infection can lead to cognitive slowing in SCZ.Methods: Fourty-seven SCZ subjects and 30 controls (CON) were tested on a standard acoustic startle paradigm. Kynurenine pathway metabolites were measured using liquid chromatography-tandem mass spectrometry were kynurenine (KYN), tryptophan (TRYP), 3-hydroxyanthranilic acid (3-OHAA), anthranilic acid (AA), and kynurenic acid (KYNA). TOXO status was determined by IgG ELISA.Results: In univariate ANCOVAs on onset and peak latency with age and log transformed startle magnitude as covariates, both onset latency [F(1,61) = 5.76; p = 0.019] and peak latency [F(1,61) = 4.34; p = 0.041] were slower in SCZ than CON subjects. In stepwise backward linear regressions after stratification by Diagnosis, slower onset latency in SCZ subjects was predicted by higher TRYP (B = 0.42; p = 0.008) and 3-OHAA:AA (B = 3.68; p = 0.007), and lower KYN:TRYP (B = −185.42; p = 0.034). In regressions with peak latency as the dependent variable, slower peak latency was predicted by higher TRYP (B = 0.47; p = 0.013) and 3-OHAA:AA ratio (B = 4.35; p = 0.010), and by lower KYNA (B = −6.67; p = 0.036). In CON subjects neither onset nor peak latency was predicted by any KYN metabolites. In regressions stratified by TOXO status, in TOXO positive subjects, slower peak latency was predicted by lower concentrations of KYN (B = −8.08; p = 0.008), KYNA (B = −10.64; p = 0.003), and lower KYN:TRYP ratios (B = −347.01; p = 0.03). In TOXO negative subjects neither onset nor peak latency was predicted by any KYN metabolites.Conclusions: KYN pathway markers predict slowing of startle latency in SCZ subjects and in those with chronic TOXO infection, but this is not seen in CON subjects nor TOXO seronegative subjects. These findings coupled with prior work indicating a relationship of slower latency with SCZ and TOXO infection suggest that alterations in KYN pathway markers may be a mechanism by which neural processing speed, as indexed by startle latency, is affected in these subjects.

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Toxoplasma gondii Effects on the Relationship of Kynurenine Pathway Metabolites to Acoustic Startle Latency in Schizophrenia vs. Control Subjects

et al. 2020

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“…Cadenhead [46] found that a small sample of CHR-C had greater PPI than CHR-NC. Since 2019, Cadenhead et al [64] have published on a larger cohort from the NAPLS2 sample and did not find any PPI differences between CHR-C and CHR-NC but, within the CHR-C sample, age was significantly correlated with PPI (greater with advancing age and not typical of normally developing adolescents), replicating a previous age finding [46], that provided evidence of neurodevelopmental differences in the sample who later converted to psychosis. In addition, the startle response latency, a measure of neural processing speed, was greater in CHR-C compared to CHR-NC, with greater predictive power than clinical symptoms in predicting future psychosis in female CHR.…”

Section: Biomarkers Linked To Psychotic Conversionmentioning

confidence: 71%

“…Dickins et al [107] used a machine learning approach to develop a model using serum lipids and was able to differentiate CHR-C from CHR-NC groups. Cadenhead et al [64] added startle response latency to the clinical symptoms used in the NAPLS Psychosis Risk Calculator and found that in female CHR startle latency had a higher AUC than the clinical symptoms in predicting psychosis. Furthermore, Worthington et al [105] included salivary cortisol in the NAPLS Psychosis Risk Calculator and achieved a good C-index.…”

Section: Prediction Modelsmentioning

confidence: 99%

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

Caballero,

Machiraju,

Diomino

et al. 2023

Curr Psychiatry Rep

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Purpose of Review This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis. Recent Findings Meta-analyses highlight conversion rates between 20 and 30% within 2–3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Summary Ongoing initiatives that assess longer-term (> 5–10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.

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Authors' reply to comments on: Recreational cannabis use over time in individuals at clinical high risk for psychosis: Lack of associations with symptom, neurocognitive, functioning, and treatment patterns

Cornblatt,

McFarlane,

Carrión

2023

Psychiatry Research

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Evidence of Slow Neural Processing, Developmental Differences and Sensitivity to Cannabis Effects in a Sample at Clinical High Risk for Psychosis From the NAPLS Consortium Assessed With the Human Startle Paradigm

Cited by 4 publications

References 60 publications

Toxoplasma gondii Effects on the Relationship of Kynurenine Pathway Metabolites to Acoustic Startle Latency in Schizophrenia vs. Control Subjects

Toxoplasma gondii Effects on the Relationship of Kynurenine Pathway Metabolites to Acoustic Startle Latency in Schizophrenia vs. Control Subjects

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

Authors' reply to comments on: Recreational cannabis use over time in individuals at clinical high risk for psychosis: Lack of associations with symptom, neurocognitive, functioning, and treatment patterns

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