Is schizophrenia associated with an increased risk of chronic kidney disease? A nationwide matched-cohort study

Tzeng, Nian Sheng; Hsu, Yung Ho; Ho, Shinn-Ying; Kuo, Yu Ching; Lee, Hua Chin; Yin, Yun Ju; Chen, Hong An; Chen, Wen Liang; Chu, William C.; Huang, Hui Ling

doi:10.1136/bmjopen-2014-006777

Cited by 47 publications

(40 citation statements)

References 36 publications

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“…23 , 24 However, there has been limited research investigating the prevalence of, and risk factors for, CKD in people with SMI. 13 , 25 , 26 In the UK, primary care plays an important role in the management of physical health conditions in people with SMI. As part of the Quality and Outcomes Framework (QOF), there have been recent financial incentives for general practitioners (GPs) to undertake physical health checks in people with SMI.…”

Section: Introductionmentioning

confidence: 99%

Severe mental illness and chronic kidney disease: a cross-sectional study in the United Kingdom

Iwagami¹,

Mansfield²,

Hayes³

et al. 2018

CLEP

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ObjectiveWe investigated the burden of chronic kidney disease (CKD) among patients with severe mental illness (SMI).MethodsWe identified patients with SMI among all those aged 25–74 registered in the UK Clinical Practice Research Datalink as on March 31, 2014. We compared the prevalence of CKD (two measurements of estimated glomerular filtration rate <60 mL/min/1.73 m2 for ≥3 months) and renal replacement therapy between patients with and without SMI. For patients with and without a history of lithium prescription separately, we used logistic regression to examine the association between SMI and CKD, adjusting for demographics, lifestyle characteristics, and known CKD risk factors.ResultsThe CKD prevalence was 14.6% among patients with SMI and a history of lithium prescription (n = 4,295), 3.3% among patients with SMI and no history of lithium prescription (n = 24,101), and 2.1% among patients without SMI (n = 2,387,988; P < 0.001). The prevalence of renal replacement therapy was 0.23%, 0.15%, and 0.11%, respectively (P = 0.012). Compared to patients without SMI, the fully adjusted odds ratio for CKD was 6.49 (95% CI 5.84–7.21) for patients with SMI and a history of lithium prescription and 1.45 (95% CI 1.34–1.58) for patients with SMI and no history of lithium prescription. The higher prevalence of CKD in patients with SMI may, in part, be explained by more frequent blood testing as compared to the general population.ConclusionCKD is identified more commonly among patients with SMI than in the general population.

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Section: Introductionmentioning

confidence: 99%

Severe mental illness and chronic kidney disease: a cross-sectional study in the United Kingdom

Iwagami¹,

Mansfield²,

Hayes³

et al. 2018

CLEP

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“…Se postula que es la misma disfunción endotelial que predispone a los pacientes a desarrollar otras enfermedades como DM2 y HTA la que estaría causando la ERC, sin embargo, se necesita más investigación en el área. Se sugiere entonces buscar dirigidamente ERC en los pacientes con EQZ y manejar las comorbilidades para prevenirla 42 .…”

Section: Enfermedad Renal Crónicaunclassified

Esquizofrenia y su asociación con enfermedades médicas crónicas

et al. 2017

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The life expectancy of patients with schizophrenia (SCH) is 11 to 20 years less than the general population. There is an association between SCH and various diseases and chronic conditions, highlighting the cardio-metabolic diseases. This association has been attributed to the use of antipsychoticsSe caracteriza por síntomas positivos (alucinaciones, delirio, síntomas catatónicos y discurso desorganizado), negativos (aplanamiento afectivo y anhedonia) y disfunciones cognitivas (alteración de atención, memoria y funciones ejecutivas) 1 . Además, hay perturbaciones fisiológicas severas que aumentan la gravedad de la EQZ, de hecho, se evidencian alteraciones endocrinológicas, del sueño, cardiovasculares y metabólicas con alteración del peso, regulación de glicemia, metabolismo lipídico y presión arterial, cuyos mecanismos no se conocen del todo 2 .La expectativa de vida de los pacientes con EQZ es entre 11 y 20 años menor que la población general y la mortalidad cardiovascular ha aumentado en este grupo de pacientes, en contraste a la población general 3 .El tratamiento antipsicótico siempre se ha asociado a estas alteraciones cardiometabólicas, sin embargo, la evidencia muestra que pacientes que nunca han recibido tratamiento también presentan estas patologías concomitantes 4 , además que muchas de ellas se encuentran desde el primer episodio psicótico, por ende, se postula que la EQZ per se estaría relacionada con esta alteración 5,6 .Este trabajo pretende actualizar los conocimientos con respecto a comorbilidades médicas crónicas asociadas a la EQZ y ayudar así a optimizar el manejo clínico de estos pacientes.

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“…Moreover, recurrent evidence exists linking microtubules/cytoskeleton and SCZ [72][73][74][75][76][77][78]. There is not much evidence for kidney development and SCZ, but there have been studies showing that SCZ is associated with chronic kidney disease, even after controlling for demographic, behavioral, and medical risk factors [79,80]. Furthermore, a study found a polygenic signature differentiating SCZ from controls, which could also significantly differentiate type 2 diabetes patients from controls by predicting a glycemic control indicator, supporting a molecular commonality between SCZ and type 2 diabetes [81].…”

Section: Discussionmentioning

confidence: 99%

Machine learning analysis of exome trios to contrast the genomic architecture of autism and schizophrenia

Sardaar

Dionne‐Laporte

et al. 2020

BMC Psychiatry

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Background: Machine learning (ML) algorithms and methods offer great tools to analyze large complex genomic datasets. Our goal was to compare the genomic architecture of schizophrenia (SCZ) and autism spectrum disorder (ASD) using ML. Methods: In this paper, we used regularized gradient boosted machines to analyze whole-exome sequencing (WES) data from individuals SCZ and ASD in order to identify important distinguishing genetic features. We further demonstrated a method of gene clustering to highlight which subsets of genes identified by the ML algorithm are mutated concurrently in affected individuals and are central to each disease (i.e., ASD vs. SCZ "hub" genes).Results: In summary, after correcting for population structure, we found that SCZ and ASD cases could be successfully separated based on genetic information, with 86-88% accuracy on the testing dataset. Through bioinformatic analysis, we explored if combinations of genes concurrently mutated in patients with the same condition ("hub" genes) belong to specific pathways. Several themes were found to be associated with ASD, including calcium ion transmembrane transport, immune system/inflammation, synapse organization, and retinoid metabolic process. Moreover, ion transmembrane transport, neurotransmitter transport, and microtubule/ cytoskeleton processes were highlighted for SCZ. Conclusions: Our manuscript introduces a novel comparative approach for studying the genetic architecture of genetically related diseases with complex inheritance and highlights genetic similarities and differences between ASD and SCZ.

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Is schizophrenia associated with an increased risk of chronic kidney disease? A nationwide matched-cohort study

Cited by 47 publications

References 36 publications

Severe mental illness and chronic kidney disease: a cross-sectional study in the United Kingdom

Severe mental illness and chronic kidney disease: a cross-sectional study in the United Kingdom

Esquizofrenia y su asociación con enfermedades médicas crónicas

Machine learning analysis of exome trios to contrast the genomic architecture of autism and schizophrenia

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