Publications by authors named "Mirko Manchia"

112 Publications

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders.

Sci Rep 2021 Sep 8;11(1):17823. Epub 2021 Sep 8.

Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan.

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
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http://dx.doi.org/10.1038/s41598-021-97140-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426488PMC
September 2021

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders.

Sci Rep 2021 Sep 8;11(1):17823. Epub 2021 Sep 8.

Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan.

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
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http://dx.doi.org/10.1038/s41598-021-97140-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426488PMC
September 2021

Leukocytosis Associated with Clozapine Treatment: A Case Series and Systematic Review of the Literature.

Medicina (Kaunas) 2021 Aug 11;57(8). Epub 2021 Aug 11.

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09124 Cagliari, Italy.

Background And Objectives: Clozapine is the only antipsychotic approved for treatment-resistant schizophrenia. Despite its superior efficacy profile as compared with other antipsychotics, clozapine remains underutilized. Clozapine monitoring systems clearly describe the proposed management of clozapine-induced neutropenia; however, no specific mention is made of how to interpret neutrophilic leukocytosis, despite that being a relatively frequent finding. Prescribers unfamiliar with this molecule may misjudge its clinical significance, potentially leading to untimely treatment interruption. Here, we systematically review the literature on the risk of neutrophilic leukocytosis during clozapine treatment, and describe eight additional cases among our patient cohort.

Materials And Methods: We performed a systematic review of the literature on PubMed and Embase using the PRISMA 2020 guidelines, and selected all original reports describing either (1) the prevalence of neutrophilic leukocytosis during clozapine treatment, or (2) the clinical significance of neutrophilic leukocytosis. We described eight additional cases of neutrophilic leukocytosis during clozapine treatment while attending an outpatient psychiatric clinic.

Results: Our research ultimately yielded the selection of 13 articles included in this systematic review. The case series highlighted the presence of stable and clinically unremarkable neutrophilia during a follow-up ranging from one to ten years.

Conclusions: Existing evidence indicates that leukocytosis associated with clozapine treatment can be considered as an asymptomatic and benign condition, suggesting that no change in clozapine treatment is needed upon its detection.
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http://dx.doi.org/10.3390/medicina57080816DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399375PMC
August 2021

Involvement of Gut Microbiota in Schizophrenia and Treatment Resistance to Antipsychotics.

Biomedicines 2021 Jul 23;9(8). Epub 2021 Jul 23.

Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09127 Cagliari, Italy.

The gut microbiota is constituted by more than 40,000 bacterial species involved in key processes including high order brain functions. Altered composition of gut microbiota has been implicated in psychiatric disorders and in modulating the efficacy and safety of psychotropic medications. In this work we characterized the composition of the gut microbiota in 38 patients with schizophrenia (SCZ) and 20 healthy controls (HC), and tested if SCZ patients with different response to antipsychotics (18 patients with treatment resistant schizophrenia (TRS), and 20 responders (R)) had specific patterns of gut microbiota composition associated with different response to antipsychotics. Moreover, we also tested if patients treated with typical antipsychotics (n = 20) presented significant differences when compared to patients treated with atypical antipsychotics (n = 31). Our findings showed the presence of distinct composition of gut microbiota in SCZ versus HC, with several bacteria at the different taxonomic levels only present in either one group or the other. Similar findings were observed also depending on treatment response and exposure to diverse classes of antipsychotics. Our results suggest that composition of gut microbiota could constitute a biosignatures of SCZ and TRS.
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http://dx.doi.org/10.3390/biomedicines9080875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8389684PMC
July 2021

Duration of untreated illness and bipolar disorder: time for a new definition? Results from a cross-sectional study.

J Affect Disord 2021 Nov 22;294:513-520. Epub 2021 Jul 22.

Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, 170 Villarroel st, 12-0, 08036, Barcelona, Catalonia, Spain.

Background: We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD).

Methods: 261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (<24 months) or long DUI. Differences in FAST scores among good (GR; TS≥7), poor (PR; TS=2-6), or non-responders (NR; TS<2) to each mood-stabilizer were analyzed. Linear regression was computed using the FAST global score as the dependent variable.

Results: DUI and FAST scores showed no statistically significant correlation. Patients with a longer DUI showed poorer response to lithium (Z=-3.196; p<0.001), but not to valproate or lamotrigine. Response to lithium (β=-1.814; p<0.001), number of hospitalizations (β=0.237; p<0.001), and illness duration (β=0.160; p=0.028) were associated with FAST total scores. GR to lithium was associated with better global functioning compared to PR or NR [H=27.631; p<0.001].

Limitations: The retrospective design could expose our data to a recall bias. Also, only few patients were on valproate or lamotrigine treatment.

Conclusions: Poor functioning in BD could be the result of multiple affective relapses, rather than a direct effect of DUI. A timely diagnosis with subsequent effective prophylactic treatment, such as lithium, may prevent poor functional outcomes in real-world patients with BD.
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http://dx.doi.org/10.1016/j.jad.2021.07.062DOI Listing
November 2021

Duration of untreated illness and bipolar disorder: time for a new definition? Results from a cross-sectional study.

J Affect Disord 2021 Nov 22;294:513-520. Epub 2021 Jul 22.

Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, 170 Villarroel st, 12-0, 08036, Barcelona, Catalonia, Spain.

Background: We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD).

Methods: 261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (<24 months) or long DUI. Differences in FAST scores among good (GR; TS≥7), poor (PR; TS=2-6), or non-responders (NR; TS<2) to each mood-stabilizer were analyzed. Linear regression was computed using the FAST global score as the dependent variable.

Results: DUI and FAST scores showed no statistically significant correlation. Patients with a longer DUI showed poorer response to lithium (Z=-3.196; p<0.001), but not to valproate or lamotrigine. Response to lithium (β=-1.814; p<0.001), number of hospitalizations (β=0.237; p<0.001), and illness duration (β=0.160; p=0.028) were associated with FAST total scores. GR to lithium was associated with better global functioning compared to PR or NR [H=27.631; p<0.001].

Limitations: The retrospective design could expose our data to a recall bias. Also, only few patients were on valproate or lamotrigine treatment.

Conclusions: Poor functioning in BD could be the result of multiple affective relapses, rather than a direct effect of DUI. A timely diagnosis with subsequent effective prophylactic treatment, such as lithium, may prevent poor functional outcomes in real-world patients with BD.
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http://dx.doi.org/10.1016/j.jad.2021.07.062DOI Listing
November 2021

Protocol for a pharmacogenetic study of antidepressants: characterization of drug-metabolizing profiles of cytochromes CYP2D6 and CYP2C19 in a Sardinian population of patients with major depressive disorder.

Psychiatr Genet 2021 Jul 16. Epub 2021 Jul 16.

Unit of Psychiatry, Department of Public Health, Clinical and Molecular Medicine, University of Cagliari Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada Unit of Clinical Pharmacology, Department of Biomedical Sciences, University Hospital Agency of Cagliari Department Economics and Business Science, Cagliari State University Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy.

The effectiveness of antidepressants shows high interindividual variability ranging from full symptomatologic remission to treatment-resistant depression. Many factors can determine the variation in the clinical response, but a fundamental role is played by genetic variation within the genes encoding for the enzymes most involved in the metabolism of antidepressant drugs: the CYP2D6 and CYP2C19 isoforms of the cytochrome P450 system. This study is poised to clarify whether the different metabolizing phenotypes related to CYP2D6 and CYP2C19 could have an impact on the clinical efficacy of antidepressants and whether the frequency of these phenotypes of metabolization shows differences in the population of Sardinian patients compared to other Caucasian populations. The sample is being recruited from patients followed-up and treated at the Psychiatric Unit of the Department of Medical Science and Public Health, University of Cagliari and the University Hospital Agency of Cagliari (Italy). The study design includes three approaches: (1) a pharmacogenetic analysis of 80 patients diagnosed with MDD resistant to antidepressant treatment compared to 80 clinically responsive or remitted patients; (2) a prospective arm (N = 30) of the study where we will test the impact of genetic variation within the CYP2D6 and CYP2C19 genes on clinical response to antidepressants and on their serum levels and (3) the assessment of the socio-economic impact of antidepressant therapies, and estimation of the cost-effectiveness of the pharmacogenetic test based on CYP genes.
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http://dx.doi.org/10.1097/YPG.0000000000000293DOI Listing
July 2021

Predominant Polarity and Polarity Index of Maintenance Treatments for Bipolar Disorder: A Validation Study in a Large Naturalistic Sample in Italy.

Medicina (Kaunas) 2021 Jun 10;57(6). Epub 2021 Jun 10.

Department of Neurosciences Rita Levi Montalcini, University of Turin, 10100 Turin, Italy.

: Predominant polarity (PP) may be a useful course specifier in at least a significant proportion of patients with Bipolar Disorder (BD), being associated with several clinically relevant correlates. Emerging evidence suggests that the concept of PP might influence the selection of maintenance treatments, based on a drug polarity index (PI) which measures the greater antidepressive vs. antimanic preventive efficacy of mood stabilizers over long-term maintenance treatment. In this study, we aimed to validate the PI in a large sample of Italian BD patients with accurate longitudinal characterization of the clinical course, which ensured a robust definition of the PP. : Our sample is comprised of 653 patients with BD, divided into groups based on the predominant polarity (manic/hypomanic predominant polarity-MPP, depressive predominant polarity-DPP and no predominant polarity). Subsequently we calculated the mean total polarity index for each group, and we compared the groups. : When we examined the mean PI of treatments prescribed to individuals with DPP, MPP and no predominant polarity, calculated using two different methods, we failed to find significant differences, with the exception of the PI calculated with the Popovic method and using the less stringent criterion for predominant polarity (PP). : Future prospective studies are needed in order to determine whether the predominant polarity is indeed one clinical factor that might guide the clinician in choosing the right mood stabilizer for BD maintenance treatment.
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http://dx.doi.org/10.3390/medicina57060598DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230357PMC
June 2021

DSM-5 and ICD-11 criteria for bipolar disorder: Implications for the prevalence of bipolar disorder and validity of the diagnosis - A narrative review from the ECNP bipolar disorders network.

Eur Neuropsychopharmacol 2021 Jun 2;47:54-61. Epub 2021 Feb 2.

Bipolar and Depressive Disorders Unit, Hospital Clinic, Institute of Neuroscience, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain.

This narrative review summarizes and discusses the implications of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and the upcoming International Classification of Diseases (ICD)-11 classification systems on the prevalence of bipolar disorder and on the validity of the DSM-5 diagnosis of bipolar disorder according to the Robin and Guze criteria of diagnostic validity. Here we review and discuss current data on the prevalence of bipolar disorder diagnosed according to DSM-5 versus DSM-IV, and data on characteristics of bipolar disorder in the two diagnostic systems in relation to extended Robin and Guze criteria: 1) clinical presentation, 2) associations with para-clinical data such as brain imaging and blood-based biomarkers, 3) delimitation from other disorders, 4) associations with family history / genetics, 5) prognosis and long-term follow-up, and 6) treatment effects. The review highlights that few studies have investigated consequences for the prevalence of the diagnosis of bipolar disorder and for the validity of the diagnosis. Findings from these studies suggest a substantial decrease in the point prevalence of a diagnosis of bipolar with DSM-5 compared with DSM-IV, ranging from 30-50%, but a smaller decrease in the prevalence during lifetime, corresponding to a 6% reduction. It is concluded that it is likely that the use of DSM-5 and ICD-11 will result in diagnostic delay and delayed early intervention in bipolar disorder. Finally, we recommend areas for future research.
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http://dx.doi.org/10.1016/j.euroneuro.2021.01.097DOI Listing
June 2021

Anatomical distribution and expression of CYP in humans: Neuropharmacological implications.

Drug Dev Res 2021 Aug 2;82(5):628-667. Epub 2021 Feb 2.

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

The cytochrome P450 (CYP450) superfamily is responsible for the metabolism of most xenobiotics and pharmacological treatments generally used in clinical settings. Genetic factors as well as environmental determinants acting through fine epigenetic mechanisms modulate the expression of CYP over the lifespan (fetal vs. infancy vs. adult phases) and in diverse organs. In addition, pathological processes might alter the expression of CYP. In this selective review, we sought to summarize the evidence on the expression of CYP focusing on three specific aspects: (a) the anatomical distribution of the expression in body districts relevant in terms of drug pharmacokinetics (liver, gut, and kidney) and pharmacodynamics, focusing for the latter on the brain, since this is the target organ of psychopharmacological agents; (b) the patterns of expression during developmental phases; and (c) the expression of CYP450 enzymes during pathological processes such as cancer. We showed that CYP isoforms show distinct patterns of expression depending on the body district and the specific developmental phases. Of particular relevance for neuropsychopharmacology is the complex regulatory mechanisms that significantly modulate the complexity of the pharmacokinetic regulation, including the concentration of specific CYP isoforms in distinct areas of the brain, where they could greatly affect local substrate and metabolite concentrations of drugs.
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http://dx.doi.org/10.1002/ddr.21778DOI Listing
August 2021

The Role of Gut Microbiota in the High-Risk Construct of Severe Mental Disorders: A Mini Review.

Front Psychiatry 2020 12;11:585769. Epub 2021 Jan 12.

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

Severe mental disorders (SMD) are highly prevalent psychiatric conditions exerting an enormous toll on society. Therefore, prevention of SMD has received enormous attention in the last two decades. Preventative approaches are based on the knowledge and detailed characterization of the developmental stages of SMD and on risk prediction. One relevant biological component, so far neglected in high risk research, is microbiota. The human microbiota consists in the ensemble of microbes, including viruses, bacteria, and eukaryotes, that inhabit several ecological niches of the organism. Due to its demonstrated role in modulating illness and health, as well in influencing behavior, much interest has focused on the characterization of the microbiota inhabiting the gut. Several studies in animal models have shown the early modifications in the gut microbiota might impact on neurodevelopment and the onset of deficits in social behavior corresponding to distinct neurosignaling alterations. However, despite this evidence, only one study investigated the effect of altered microbiome and risk of developing mental disorders in humans, showing that individuals at risk for SMD had significantly different global microbiome composition than healthy controls. We then offer a developmental perspective and provided mechanistic insights on how changes in the microbiota could influence the risk of SMD. We suggest that the analysis of microbiota should be included in the comprehensive assessment generally performed in populations at high risk for SMD as it can inform predictive models and ultimately preventative strategies.
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http://dx.doi.org/10.3389/fpsyt.2020.585769DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835325PMC
January 2021

Overview of CAPICE-Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Skłodowska-Curie International Training Network.

Eur Child Adolesc Psychiatry 2021 Jan 20. Epub 2021 Jan 20.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).
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http://dx.doi.org/10.1007/s00787-020-01713-2DOI Listing
January 2021

Prediction of lithium response using genomic data.

Sci Rep 2021 01 13;11(1):1155. Epub 2021 Jan 13.

Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.
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http://dx.doi.org/10.1038/s41598-020-80814-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806976PMC
January 2021

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder.

Transl Psychiatry 2021 01 11;11(1):36. Epub 2021 Jan 11.

Department of Psychiatry, Charles University, Prague, Czech Republic.

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.
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http://dx.doi.org/10.1038/s41398-020-01148-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801503PMC
January 2021

[Clinical, diagnostic and forensic features of a REMS patient's sample].

Riv Psichiatr 2020 Nov-Dec;55(6):15-19

Dipartimento di Scienze Mediche, Chirurgiche e Sperimentali, Università di Sassari.

Introduction: Residential Services for the Execution of Security Measures (REMS) are specialist psychiatric units for forensic patients created in 2015 after OPG (Italian Security Psychiatric Forensic Hospitals) have been closed.

Aims: to describe the clinical, diagnostic and forensic features of patients and evaluate the relevance of 3 elements: use of alcohol and substance, antisociality, cognitive disability. A further aim is the evaluation of the level of pre and post admission diagnostic concordance.

Methods: A specific database has been set for the purpose of the study, which collects data of patients admitted in 5 years of activity of the unit. Data have been analysed through a descriptive approach.

Results: 4 main clusters have been identified: Psychosis, Use of Alcohol/Substance Disorder, Personality Disorder, Cognitive Disability. Alcohol/substance use, antisociality, cognitive disability elements are relevant in the sample. Diagnostic concordance level pre- and post- admission is overall good, sometimes partial.

Conclusions: alcohol/substance use, antisociality and cognitive disability, often in comorbidity mode, represent core features in part of the sample. This finding emphasizes a complexity level which is linked to social and judicial aspects, in addition to the health component.
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http://dx.doi.org/10.1708/3504.34901DOI Listing
December 2020

Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.

Per Med 2021 01 30;18(1):75-90. Epub 2020 Oct 30.

Department of Surgical Sciences, Neonatal Intensive Care Unit, Neonatal Pathology & Neonatal Section, University of Cagliari, Cagliari, Italy.

There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.
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http://dx.doi.org/10.2217/pme-2020-0033DOI Listing
January 2021

Prevalence and clinical correlates of cognitive symptoms in depression: a naturalistic study.

Riv Psichiatr 2020 Sep-Oct;55(5):301-307

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Italy.

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http://dx.doi.org/10.1708/3457.34463DOI Listing
October 2020

The biology of aggressive behavior in bipolar disorder: A systematic review.

Neurosci Biobehav Rev 2020 12 24;119:9-20. Epub 2020 Sep 24.

Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, 170 Villarroel St, 12-0, 08036, Barcelona, Catalonia, Spain.

Aggressive behavior (AB) represents a public health concern often associated with severe psychiatric disorders. Although most psychiatric patients are not aggressive, untreated psychiatric illness, including bipolar disorder (BD), may associate with an increased risk of AB. Accurate predictive models of AB are still lacking and it is crucial to delineate AB biomarkers state of the art in BD. We performed a systematic review according to PRISMA guidelines to identify biological correlates of AB in BD. Final results included 20 studies: 10 involving genetic and 10 other biological AB biomarkers (total sample size N = 5,181). Our results pointed to a serotoninergic hypoactivation in violent suicidal BD patients. Similarly, BD violent suicide attempters had a blunted hypothalamic-pituitary-adrenal (HPA) activity. Violent behavior in BD was associated with a chronic inflammatory state. While the role of lipids as biomarkers for AB remains equivocal, uric acid appears as a potential biomarker for hetero-AB in BD. Available data can be useful in the fulfill of specific biomarkers of AB in BD, ultimately leading to the development of accurate predictive models.
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http://dx.doi.org/10.1016/j.neubiorev.2020.09.015DOI Listing
December 2020

Telomere attrition and inflammatory load in severe psychiatric disorders and in response to psychotropic medications.

Neuropsychopharmacology 2020 12 12;45(13):2229-2238. Epub 2020 Sep 12.

Unit of Psychiatry, Department of Public Health, Clinical and Molecular Medicine, University of Cagliari, Cagliari, Italy.

Individuals with severe psychiatric disorders have a reduced life expectancy compared to the general population. At the biological level, patients with these disorders present features that suggest the involvement of accelerated aging, such as increased circulating inflammatory markers and shorter telomere length (TL). To date, the role of the interplay between inflammation and telomere dynamics in the pathophysiology of severe psychiatric disorders has been scarcely investigated. In this study we measured T-lymphocytes TL with quantitative fluorescent in situ hybridization (Q-FISH) and plasma levels of inflammatory markers in a cohort comprised of 40 patients with bipolar disorder (BD), 41 with schizophrenia (SZ), 37 with major depressive disorder (MDD), and 36 non-psychiatric controls (NPC). TL was shorter in SZ and in MDD compared to NPC, while it was longer in BD (model F = 20.128, p = 8.73 × 10, effect of diagnosis, F = 31.870; p = 1.08 × 10). There was no effect of the different classes of psychotropic medications, while duration of treatment with mood stabilizers was associated with longer TL (Partial correlation controlled for age and BMI: correlation coefficient = 0.451; p = 0.001). Levels of high-sensitivity C-Reactive Protein (hsCRP) were higher in SZ compared to NPC (adjusted p = 0.027), and inversely correlated with TL in the whole sample (r = -0.180; p = 0.042). Compared to NPC, patients with treatment resistant (TR) SZ had shorter TL (p = 0.001), while patients with TR MDD had higher levels of tumor necrosis factor-α (TNFα) compared to NPC (p = 0.028) and to non-TR (p = 0.039). Comorbidity with cardio-metabolic disorders did not influence the observed differences in TL, hsCRP, and TNFα among the diagnostic groups. Our study suggests that patients with severe psychiatric disorders present reduced TL and increased inflammation.
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http://dx.doi.org/10.1038/s41386-020-00844-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7784910PMC
December 2020

Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment.

Medicina (Kaunas) 2020 Sep 8;56(9). Epub 2020 Sep 8.

Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, 09042 Cagliari, Italy.

Futurists have anticipated that novel autonomous technologies, embedded with machine learning (ML), will substantially influence healthcare. ML is focused on making predictions as accurate as possible, while traditional statistical models are aimed at inferring relationships between variables. The benefits of ML comprise flexibility and scalability compared with conventional statistical approaches, which makes it deployable for several tasks, such as diagnosis and classification, and survival predictions. However, much of ML-based analysis remains scattered, lacking a cohesive structure. There is a need to evaluate and compare the performance of well-developed conventional statistical methods and ML on patient outcomes, such as survival, response to treatment, and patient-reported outcomes (PROs). In this article, we compare the usefulness and limitations of traditional statistical methods and ML, when applied to the medical field. Traditional statistical methods seem to be more useful when the number of cases largely exceeds the number of variables under study and a priori knowledge on the topic under study is substantial such as in public health. ML could be more suited in highly innovative fields with a huge bulk of data, such as omics, radiodiagnostics, drug development, and personalized treatment. Integration of the two approaches should be preferred over a unidirectional choice of either approach.
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http://dx.doi.org/10.3390/medicina56090455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560135PMC
September 2020

Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants.

Biomedicines 2020 Aug 27;8(9). Epub 2020 Aug 27.

Fondazione IRCCS Casa Sollievo della Sofferenza Hospital, Division of Gastroenterology, 71013 San Giovanni Rotondo, Italy.

Major depressive disorder (MDD) is a common severe psychiatric illness, exhibiting sub-optimal response to existing pharmacological treatments. Although its etiopathogenesis is still not completely understood, recent findings suggest that an altered composition of the gut microbiota might play a role. Here we aimed to explore potential differences in the composition of the gut microbiota between patients with MDD and healthy controls (HC) and to identify possible signatures of treatment response by analyzing two groups of MDD patients characterized as treatment-resistant (TR) or responders (R) to antidepressants. Stool samples were collected from 34 MDD patients (8 TR, 19 R and 7 untreated) and 20 HC. Microbiota was characterized using the 16S metagenomic approach. A penalized logistic regression analysis algorithm was applied to identify bacterial populations that best discriminate the diagnostic groups. Statistically significant differences were identified for the families of and , for the genus , and the species , , and among others. The phyla and the family were more abundant in TR, whereas the phylum was enriched in R patients. Moreover, a number of bacteria only characterized the microbiota of TR patients, and many others were only detected in R. Our results confirm that dysbiosis is a hallmark of MDD and suggest that microbiota of TR patients significantly differs from responders to antidepressants. This finding further supports the relevance of an altered composition of the gut microbiota in the etiopathogenesis of MDD, suggesting a role in response to antidepressants.
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http://dx.doi.org/10.3390/biomedicines8090311DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554953PMC
August 2020

Copper-Induced Epigenetic Changes Shape the Clinical Phenotype in Wilson's Disease.

Curr Med Chem 2021 ;28(14):2707-2716

Section of Pathology, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

Wilson's disease is a congenital disorder of copper metabolism whose pathogenesis remains, at least in part, unknown. Subjects carrying the same genotype may show completely different phenotypes, differing for the age at illness onset or for the hepatic, neurologic or psychiatric clinical presentation. The inability to find a unequivocal correlation between the type of mutation in the ATPase copper transporting beta (ATP7B) gene and the phenotypic manifestation, has encouraged many authors to look for epigenetic factors interacting with the genetic changes. Here, the evidences regarding the ability of copper overload to change the global DNA methylation status are discussed.
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http://dx.doi.org/10.2174/0929867327666200730214757DOI Listing
June 2021

Editorial: Decreasing the Impact of Treatment Resistance in Schizophrenia: Identifying Novel Molecular Targets/Pathways to Increase Treatment Efficacy.

Front Pharmacol 2020 2;11:1001. Epub 2020 Jul 2.

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

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http://dx.doi.org/10.3389/fphar.2020.01001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346737PMC
July 2020

Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action.

Eur Neuropsychopharmacol 2020 07 12;36:121-136. Epub 2020 Jun 12.

NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address:

Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identification of the underlying pathophysiology for BD is fundamental to realize major health benefits through better treatment and preventive regimens. However, to achieve these goals requires coordinated action and innovative approaches to boost the discovery of the neurobiological underpinnings of BD, and rapid translation of research findings into development and testing of better and more specific treatments. To this end, we here propose that only a large-scale coordinated action can be successful in integrating international big-data approaches with real-world clinical interventions. This could be achieved through the creation of a Global Bipolar Disorder Foundation, which could bring government, industry and philanthropy together in common cause. A global initiative for BD research would come at a highly opportune time given the seminal advances promised for our understanding of the genetic and brain basis of the disease and the obvious areas of unmet clinical need. Such an endeavour would embrace the principles of open science and see the strong involvement of user groups and integration of dissemination and public involvement with the research programs. We believe the time is right for a step change in our approach to understanding, treating and even preventing BD effectively.
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http://dx.doi.org/10.1016/j.euroneuro.2020.05.006DOI Listing
July 2020

Glycine Signaling in the Framework of Dopamine-Glutamate Interaction and Postsynaptic Density. Implications for Treatment-Resistant Schizophrenia.

Front Psychiatry 2020 14;11:369. Epub 2020 May 14.

Laboratory of Molecular Psychiatry and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Odontostomatology, University School of Medicine of Napoli Federico II, Naples, Italy.

Treatment-resistant schizophrenia (TRS) or suboptimal response to antipsychotics affects almost 30% of schizophrenia (SCZ) patients, and it is a relevant clinical issue with significant impact on the functional outcome and on the global burden of disease. Among putative novel treatments, glycine-centered therapeutics (i.e. sarcosine, glycine itself, D-Serine, and bitopertin) have been proposed, based on a strong preclinical rationale with, however, mixed clinical results. Therefore, a better appraisal of glycine interaction with the other major players of SCZ pathophysiology and specifically in the framework of dopamine - glutamate interactions is warranted. New methodological approaches at cutting edge of technology and drug discovery have been applied to study the role of glycine in glutamate signaling, both at presynaptic and post-synaptic level and have been instrumental for unveiling the role of glycine in dopamine-glutamate interaction. Glycine is a non-essential amino acid that plays a critical role in both inhibitory and excitatory neurotransmission. In caudal areas of central nervous system (CNS), such as spinal cord and brainstem, glycine acts as a powerful inhibitory neurotransmitter through binding to its receptor, i.e. the Glycine Receptor (GlyR). However, glycine also works as a co-agonist of the N-Methyl-D-Aspartate receptor (NMDAR) in excitatory glutamatergic neurotransmission. Glycine concentration in the synaptic cleft is finely tuned by glycine transporters, i.e. GlyT1 and GlyT2, that regulate the neurotransmitter's reuptake, with the first considered a highly potential target for psychosis therapy. Reciprocal regulation of dopamine and glycine in forebrain, glycine modulation of glutamate, glycine signaling interaction with postsynaptic density proteins at glutamatergic synapse, and human genetics of glycinergic pathways in SCZ are tackled in order to highlight the exploitation of this neurotransmitters and related molecules in SCZ and TRS.
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http://dx.doi.org/10.3389/fpsyt.2020.00369DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7240307PMC
May 2020

Stress resilience during the coronavirus pandemic.

Eur Neuropsychopharmacol 2020 06 11;35:12-16. Epub 2020 May 11.

Department of Pschiatry, Leiden University Medical Center, Leiden, the Netherlands, Leiden Institute for Brain and Cognition, Leiden, The Netherlands.

The epidemic of the 2019 novel coronavirus SARS-CoV-2, causing the coronavirus disease 2019 (COVID-19) is a global public health emergency with multifaceted severe consequences for people's lives and their mental health. In this article, as members of the European College of Neuropsychopharmacology (ECNP) Resilience, we will discuss the urgent need for a focus on resilience during the current coronavirus pandemic. Resilience is pivotal to cope with stress and vital to stay in balance. We will discuss the importance of resilience at the individual and societal level, but also the implication for patients with a psychiatric condition and health care workers. We not only advocate for an increased focus on mental health during the coronavirus pandemic but also highlight the urgent need of augmenting our focus on resilience and on strategies to enhance it.
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http://dx.doi.org/10.1016/j.euroneuro.2020.05.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211573PMC
June 2020

Lithium's antiviral effects: a potential drug for CoViD-19 disease?

Int J Bipolar Disord 2020 May 20;8(1):21. Epub 2020 May 20.

Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Fetscherstr. 74, 01307, Dresden, Germany.

Background: Since its introduction in modern medicine, naturalistic observations emerged about possible uses of lithium treatment for conditions different from recurring affective disorders, for which it is still a first-line treatment option. Some evidence about the antiviral properties of lithium began in the early 1970s, when some reports found a reduction of labial-herpetic recurrences. The present review aims to present most of the pre-clinical and clinical evidence about lithium's ability to inhibit DNA and RNA viruses, including Coronaviridae, as well as the possible pathways and mechanisms involved in such antiviral activity.

Main Body: Despite a broad number of in vitro studies, the rationale for the antiviral activity of lithium failed to translate into methodologically sound clinical studies demonstrating its antiviral efficacy. In addition, the tolerability of lithium as an antiviral agent should be addressed. In fact, treatment with lithium requires continuous monitoring of its serum levels in order to prevent acute toxicity and long-term side effects, most notably affecting the kidney and thyroid. Yet lithium reaches heterogeneous but bioequivalent concentrations in different tissues, and the anatomical compartment of the viral infection might underpin a different, lower need for tolerability concerns which need to be addressed.

Conclusions: Lithium presents a clear antiviral activity demonstrated at preclinical level, but that remains to be confirmed in clinical settings. In addition, the pleiotropic mechanisms of action of lithium may provide an insight for its possible use as antiviral agent targeting specific pathways.
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http://dx.doi.org/10.1186/s40345-020-00191-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239605PMC
May 2020

Challenges and Future Prospects of Precision Medicine in Psychiatry.

Pharmgenomics Pers Med 2020 23;13:127-140. Epub 2020 Apr 23.

Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.
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http://dx.doi.org/10.2147/PGPM.S198225DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186890PMC
April 2020
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