Predictive Performance of Exposome Score for Schizophrenia in the General Population

Abstract Previously, we established an estimated exposome score for schizophrenia (ES-SCZ) as a cumulative measure of environmental liability for schizophrenia to use in gene–environment interaction studies and for risk stratification in population cohorts. Hereby, we examined the discriminative function of ES-SCZ for identifying individuals diagnosed with schizophrenia spectrum disorder in the general population by measuring the area under the receiver operating characteristic curve (AUC). Furthermore, we compared this ES-SCZ method to an environmental sum score (Esum-SCZ) and an aggregate environmental score weighted by the meta-analytical estimates (Emet-SCZ). We also estimated ORs and Nagelkerke’s R2 for ES-SCZ in association with psychiatric diagnoses and other medical outcomes. ES-SCZ showed a good discriminative function (AUC = 0.84) and statistically significantly performed better than both Esum-SCZ (AUC = 0.80) and Emet-SCZ (AUC = 0.80). At optimal cut point, ES-SCZ showed similar performance in ruling out (LR− = 0.20) and ruling in (LR+ = 3.86) schizophrenia. ES-SCZ at optimal cut point showed also a progressively greater magnitude of association with increasing psychosis risk strata. Among all clinical outcomes, ES-SCZ was associated with schizophrenia diagnosis with the highest OR (2.76, P < .001) and greatest explained variance (R2 = 14.03%), followed by bipolar disorder (OR = 2.61, P < .001, R2 = 13.01%) and suicide plan (OR = 2.44, P < .001, R2 = 12.44%). Our findings from an epidemiologically representative general population cohort demonstrate that an aggregate environmental exposure score for schizophrenia constructed using a predictive modeling approach—ES-SCZ—has the potential to improve risk prediction and stratification for research purposes and may help gain insight into the multicausal etiology of psychopathology.

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Urine cadmium levels and albuminuria in a general population from Spain: A gene-environment interaction analysis

Environment International ◽

10.1016/j.envint.2017.05.008 ◽

2017 ◽

Vol 106 ◽

pp. 27-36 ◽

Cited By ~ 16

Author(s):

Maria Grau-Perez ◽

Gernot Pichler ◽

Inma Galan-Chilet ◽

Laisa S. Briongos-Figuero ◽

Pilar Rentero-Garrido ◽

...

Keyword(s):

General Population ◽

Interaction Analysis ◽

Environment Interaction ◽

Gene Environment Interaction ◽

Gene Environment ◽

Urine Cadmium

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Association and Predictive Value Analysis for Resting Heart Rate and Diabetes Mellitus on Cardiovascular Autonomic Neuropathy in General Population

Journal of Diabetes Research ◽

10.1155/2014/215473 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 7

Author(s):

Zi-Hui Tang ◽

Fangfang Zeng ◽

Zhongtao Li ◽

Linuo Zhou

Keyword(s):

General Population ◽

Predictive Value ◽

Large Scale ◽

Reference Group ◽

Characteristic Curve ◽

Predictive Performance ◽

Population Based ◽

Cross Sectional Study ◽

Cross Sectional ◽

Value Analysis

Background.The purpose of this study was to evaluate the predictive value of DM and resting HR on CAN in a large sample derived from a Chinese population.Materials and Methods.We conducted a large-scale, population-based, cross-sectional study to explore the relationships of CAN with DM and resting HR. A total of 387 subjects were diagnosed with CAN in our dataset. The associations of CAN with DM and resting HR were assessed by a multivariate logistic regression (MLR) analysis (using subjects without CAN as a reference group) after controlling for potential confounding factors. The area under the receiver-operating characteristic curve (AUC) was used to evaluate the predictive performance of resting HR and DM.Results.A tendency toward increased CAN prevalence with increasing resting HR was reported (Pfor trend<0.001). MLR analysis showed that DM and resting HR were very significantly and independently associated with CAN (P<0.001for both). Resting HR alone or combined with DM (DM-HR) both strongly predicted CAN (AUC = 0.719, 95% CI 0.690–0.748 for resting HR and AUC = 0.738, 95% CI 0.710–0.766 for DM-HR).Conclusion.Our findings signify that resting HR and DM-HR have a high value in predicting CAN in the general population.

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TwinssCan — Gene-Environment Interaction in Psychotic and Depressive Intermediate Phenotypes: Risk and Protective Factors in a General Population Twin Sample

Twin Research and Human Genetics ◽

10.1017/thg.2019.96 ◽

2019 ◽

Vol 22 (6) ◽

pp. 460-466 ◽

Cited By ~ 1

Author(s):

Lotta-Katrin Pries ◽

Clara Snijders ◽

Claudia Menne-Lothmann ◽

Jeroen Decoster ◽

Ruud van Winkel ◽

...

Keyword(s):

General Population ◽

Social Defeat ◽

Reward Sensitivity ◽

Environment Interaction ◽

Affective Dysregulation ◽

Intermediate Phenotypes ◽

Gene Environment ◽

National Networks ◽

Meta Analyses ◽

Adult Twins

AbstractMeta-analyses suggest that clinical psychopathology is preceded by dimensional behavioral and cognitive phenotypes such as psychotic experiences, executive functioning, working memory and affective dysregulation that are determined by the interplay between genetic and nongenetic factors contributing to the severity of psychopathology. The liability to mental ill health can be psychometrically measured using experimental paradigms that assess neurocognitive processes such as salience attribution, sensitivity to social defeat and reward sensitivity. Here, we describe the TwinssCan, a longitudinal general population twin cohort, which comprises 1202 individuals (796 adolescent/young adult twins, 43 siblings and 363 parents) at baseline. The TwinssCan is part of the European Network of National Networks studying Gene-Environment Interactions in Schizophrenia project and recruited from the East Flanders Prospective Twin Survey. The main objective of this project is to understand psychopathology by evaluating the contribution of genetic and nongenetic factors on subclinical expressions of dimensional phenotypes at a young age before the onset of disorder and their association with neurocognitive processes, such as salience attribution, sensitivity to social defeat and reward sensitivity.

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Genome-Wide Meta-Analysis Unravels Interactions between Magnesium Homeostasis and Metabolic Phenotypes

Journal of the American Society of Nephrology ◽

10.1681/asn.2017030267 ◽

2017 ◽

Vol 29 (1) ◽

pp. 335-348 ◽

Cited By ~ 13

Author(s):

Tanguy Corre ◽

Francisco J. Arjona ◽

Caroline Hayward ◽

Sonia Youhanna ◽

Jeroen H.F. de Baaij ◽

...

Keyword(s):

General Population ◽

Meta Analysis ◽

Human Kidney ◽

Environment Interaction ◽

Genetic Determinants ◽

Metabolic Disturbances ◽

Renal Handling ◽

Gene Environment ◽

Genome Wide ◽

A Genome

Magnesium (Mg2+) homeostasis is critical for metabolism. However, the genetic determinants of the renal handling of Mg2+, which is crucial for Mg2+ homeostasis, and the potential influence on metabolic traits in the general population are unknown. We obtained plasma and urine parameters from 9099 individuals from seven cohorts, and conducted a genome-wide meta-analysis of Mg2+ homeostasis. We identified two loci associated with urinary magnesium (uMg), rs3824347 (P=4.4×10−13) near TRPM6, which encodes an epithelial Mg2+ channel, and rs35929 (P=2.1×10−11), a variant of ARL15, which encodes a GTP-binding protein. Together, these loci account for 2.3% of the variation in 24-hour uMg excretion. In human kidney cells, ARL15 regulated TRPM6-mediated currents. In zebrafish, dietary Mg2+ regulated the expression of the highly conserved ARL15 ortholog arl15b, and arl15b knockdown resulted in renal Mg2+ wasting and metabolic disturbances. Finally, ARL15 rs35929 modified the association of uMg with fasting insulin and fat mass in a general population. In conclusion, this combined observational and experimental approach uncovered a gene–environment interaction linking Mg2+ deficiency to insulin resistance and obesity.

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