Publications by authors named "Martin Alda"

244 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

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

Consensus on nomenclature for clinical staging models in bipolar disorder: A narrative review from the International Society for Bipolar Disorders (ISBD) Staging Task Force.

Bipolar Disord 2021 Jun 26. Epub 2021 Jun 26.

St. Joseph's Healthcare Hamilton McMaster University, Hamilton, ON, Canada.

Objectives: Clinical staging is widely used in medicine to map disease progression, inform prognosis, and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well-defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking.

Methods: Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders.

Results: Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at-risk status and subthreshold stages, and to various clinical stages of BD as it is currently diagnosed.

Conclusion: The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light.
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http://dx.doi.org/10.1111/bdi.13105DOI Listing
June 2021

The moving target of psychiatric diagnosis.

Authors:
Martin Alda

J Psychiatry Neurosci 2021 Jun 17;46(3):E415-E417. Epub 2021 Jun 17.

From the Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.

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http://dx.doi.org/10.1503/jpn.210098DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327973PMC
June 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
March 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
March 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Therapeutic lithium alters polar head-group region of lipid bilayer and prevents lipid peroxidation in forebrain cortex of sleep-deprived rats.

Biochim Biophys Acta Mol Cell Biol Lipids 2021 09 13;1866(9):158962. Epub 2021 May 13.

Laboratory of Neurochemistry, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.

Lithium is regarded as a unique therapeutic agent for the management of bipolar disorder (BD). In efforts to explain the favourable effects of lithium in BD, a wide range of mechanisms was suggested. Among those, the effect of clinically relevant concentrations of lithium on the plasma membrane was extensively studied. However, the biophysical properties of brain membranes isolated from experimental animals exposed to acute, short-term and chronic lithium have not been performed to-date. In this study, we compared the biophysical parameters and level of lipid peroxidation in membranes isolated from forebrain cortex (FBC) of therapeutic lithium-treated and/or sleep-deprived rats. Lithium interaction with FBC membranes was characterized by appropriate fluorescent probes. DPH (1,6-diphenyl-1,3,5-hexatriene) and TMA-DPH (1-(4-trimethylammoniumphenyl)-6-phenyl-1,3,5-hexatriene p-toluenesulphonate) were used for characterization of the hydrophobic lipid core and Laurdan (6-dodecanoyl-2-dimethylaminonaphthalene) for the membrane-water interface. Lipid peroxidation was determined by immunoblot analysis of 4-HNE-(4-hydroxynonenal)-protein adducts. The organization of polar head-group region of FBC membranes, measured by Laurdan generalized polarization, was substantially altered by sleep deprivation and augmented by lithium treatment. Hydrophobic membrane interior characterized by steady-state anisotropy of DPH and TMA-DPH fluorescence was unchanged. Chronic lithium had a protective effect against peroxidative damage of membrane lipids in FBC. In summary, lithium administration at a therapeutic level and/or sleep deprivation as an animal model of mania resulted in changes in rat FBC membrane properties.
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http://dx.doi.org/10.1016/j.bbalip.2021.158962DOI Listing
September 2021

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.

Mol Psychiatry 2021 Apr 16. Epub 2021 Apr 16.

Unit for Psychosomatics / CL Outpatient Clinic for Adults, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.
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http://dx.doi.org/10.1038/s41380-021-01098-xDOI Listing
April 2021

Reduced heart rate variability is associated with higher illness burden in bipolar disorder.

J Psychosom Res 2021 Jun 30;145:110478. Epub 2021 Mar 30.

Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada.

Background: Bipolar disorder (BD) is associated with premature death and ischemic heart disease is the main cause of excess mortality. Heart rate variability (HRV) predicts mortality in patients with or without cardiovascular disease. While several studies have analyzed the association between HRV and BD, none has analyzed the association of HRV with illness burden in BD.

Methods: 53 participants with BD I and II used a wearable device to assess the association between HRV and factors characterizing illness burden, including illness duration, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, and co-morbid psychiatric disorders. We ran unadjusted models and models controlling statistically for age, sex, pharmacotherapy, baseline functional cardiovascular capacity, BMI, years of education, and marital status. We also explored the association between HRV and an overall illness burden index (IBI) integrating all these factors using a weighted geometric mean.

Results: Adjusted and unadjusted models had similar results. Longer illness duration, higher number of depressive episodes, longer duration of most severe manic/hypomanic episode, co-morbid anxiety disorders, and family history of suicide were associated with reduced HRV, as was bipolar depression severity in the participants experiencing a depressive episode. Finally, a higher IBI score was associated with lower HRV.

Conclusions: High illness burden is associated with reduced HRV in BD. While the IBI needs to be validated in a larger sample, it may provide an overall measure that captures illness burden in BD.
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http://dx.doi.org/10.1016/j.jpsychores.2021.110478DOI Listing
June 2021

Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study.

Bipolar Disord 2021 Apr 2. Epub 2021 Apr 2.

University of Michigan, Ann Arbor, MI, USA.

Background: Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response.

Methods: The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse.

Results: A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness.

Conclusions: In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy.
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http://dx.doi.org/10.1111/bdi.13078DOI Listing
April 2021

Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: preliminary studies.

Mol Psychiatry 2021 Mar 5. Epub 2021 Mar 5.

VA San Diego Healthcare System, San Diego, CA, USA.

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.
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http://dx.doi.org/10.1038/s41380-021-01048-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418615PMC
March 2021

Increasing Cybercrime Since the Pandemic: Concerns for Psychiatry.

Curr Psychiatry Rep 2021 03 3;23(4):18. Epub 2021 Mar 3.

ChronoRecord Association, Fullerton, CA, USA.

Purpose Of Review: Since the pandemic, the daily activities of many people occur at home. People connect to the Internet for work, school, shopping, entertainment, and doctor visits, including psychiatrists. Concurrently, cybercrime has surged worldwide. This narrative review examines the changing use of technology, societal impacts of the pandemic, how cybercrime is evolving, individual vulnerabilities to cybercrime, and special concerns for those with mental illness.

Recent Findings: Human factors are a central component of cybersecurity as individual behaviors, personality traits, online activities, and attitudes to technology impact vulnerability. Mental illness may increase vulnerability to cybercrime. The risks of cybercrime should be recognized as victims experience long-term psychological and financial consequences. Patients with mental illness may not be aware of the dangers of cybercrime, of risky online behaviors, or the measures to mitigate risk. Technology provides powerful tools for psychiatry but technology must be used with the appropriate safety measures. Psychiatrists should be aware of the potential aftermath of cybercrime on mental health, and the increased patient risk since the pandemic, including from online mental health services. As a first step to increase patient awareness of cybercrime, psychiatrists should provide a recommended list of trusted sources that educate consumers on cybersecurity.
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http://dx.doi.org/10.1007/s11920-021-01228-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927777PMC
March 2021

Increasing Cybercrime Since the Pandemic: Concerns for Psychiatry.

Curr Psychiatry Rep 2021 03 3;23(4):18. Epub 2021 Mar 3.

ChronoRecord Association, Fullerton, CA, USA.

Purpose Of Review: Since the pandemic, the daily activities of many people occur at home. People connect to the Internet for work, school, shopping, entertainment, and doctor visits, including psychiatrists. Concurrently, cybercrime has surged worldwide. This narrative review examines the changing use of technology, societal impacts of the pandemic, how cybercrime is evolving, individual vulnerabilities to cybercrime, and special concerns for those with mental illness.

Recent Findings: Human factors are a central component of cybersecurity as individual behaviors, personality traits, online activities, and attitudes to technology impact vulnerability. Mental illness may increase vulnerability to cybercrime. The risks of cybercrime should be recognized as victims experience long-term psychological and financial consequences. Patients with mental illness may not be aware of the dangers of cybercrime, of risky online behaviors, or the measures to mitigate risk. Technology provides powerful tools for psychiatry but technology must be used with the appropriate safety measures. Psychiatrists should be aware of the potential aftermath of cybercrime on mental health, and the increased patient risk since the pandemic, including from online mental health services. As a first step to increase patient awareness of cybercrime, psychiatrists should provide a recommended list of trusted sources that educate consumers on cybersecurity.
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http://dx.doi.org/10.1007/s11920-021-01228-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927777PMC
March 2021

Lithium from breast-milk inhibits thyroid iodine uptake and hormone production, which are remedied by maternal iodine supplementation.

Bipolar Disord 2021 Jan 28. Epub 2021 Jan 28.

Department of Physics, City University of Hong Kong, Hong Kong SAR, China.

Background: Lithium is especially taken as a maintenance medication for Bipolar Disorder. In women with bipolar disorder, lithium is often effective during postpartum period, but breast-feeding for medicated mothers is controversial because of harmful effects for her child. At present, the biological mechanisms of lithium are not well-understood, affecting its usage and overall health implications.

Procedure: We developed a rat lithium and breast-feeding model at human therapeutic levels to study the effects of lithium exposure through breast-milk on pups' thyroid function. Novel laser analytical spectroscopy, along with traditional blood and immunohistochemical tests, were applied to further investigate the mechanisms behind the thyroid dysfunction. Maternal iodine supplementation was evaluated as a therapeutic method to address the pups' thyroid dysfunction.

Results: Pups exposed to lithium via breastmilk, even with the dam on a sub-therapeutic level, experienced weight gain, reduced blood thyroxine (T ), and elevated blood urea nitrogen, indicating effects on thyroid and kidney function. We show that lithium inhibited iodine uptake by thyroid follicles, initiating a mechanism that reduced iodination of tyrosine, thyroglobulin cleavage, and thyroid hormone production. Importantly, infant thyroid function can be significantly improved by administering supplementary iodine to the medicated dam's diet during breast-feeding.

Conclusion: These results elucidate the mechanisms of lithium in thyroid function, provide valuable information on use postpartum, and suggest a clinically applicable remedy to side-effects. The results are particularly important for patients (and their infants) who respond well to lithium and need, or choose, to breast-feed.
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http://dx.doi.org/10.1111/bdi.13047DOI Listing
January 2021

Categorical differentiation of the unipolar and bipolar disorders.

Psychiatry Res 2021 03 14;297:113719. Epub 2021 Jan 14.

School of Psychiatry, University of New South Wales, Sydney, Australia; Black Dog Institute, Sydney, Australia.

There has been a longstanding debate as to whether the bipolar disorders differ categorically or dimensionally, with some dimensional or spectrum models including unipolar depressive disorders within a bipolar spectrum model. We analysed manic/hypomanic symptom data in samples of clinically diagnosed bipolar I, bipolar II and unipolar patients, employing latent class analyses to determine if separate classes could be identified. Mixture analyses were also undertaken to determine if a unimodal, bimodal or a trimodal pattern was present. For both a refined 15-item set and an extended 30-item set of manic/hypomanic symptoms, our latent class analyses favoured three-class solutions, while mixture analyses identified trimodal distributions of scores. Findings argue for a categorical distinction between unipolar and bipolar disorders, as well as between bipolar I and bipolar II disorders. Future research should aim to consolidate these results in larger samples, particularly given that the size of the unipolar group in this study was a salient limitation.
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http://dx.doi.org/10.1016/j.psychres.2021.113719DOI Listing
March 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

Tissue-specific protective properties of lithium: comparison of rat kidney, erythrocytes and brain.

Naunyn Schmiedebergs Arch Pharmacol 2021 05 6;394(5):955-965. Epub 2021 Jan 6.

Laboratory of Biomathematics, Institute of Physiology of the Czech Academy of Sciences, v.v.i., Videnska 1083, 14220, Prague 4, Czech Republic.

Lithium (Li) represents a first choice mood stabilizer for bipolar disorder (BD). Despite extensive clinical use, questions regarding its mechanism of action and pathological mechanism of renal function impairment by Li remain open. The present study aimed to improve our knowledge in this area paying special attention to the relationship between the length of Li action, lipid peroxidation (LP), and Na/K-ATPase properties. The effects of therapeutic Li doses, administered daily to male Wistar rats for 1 (acute), 7 (short term) and 28 days (chronic), were studied. For this purpose, Na/K-ATPase activity measurements, [H]ouabain binding and immunoblot analysis of α-Na/K-ATPase were performed. Li-induced LP was evaluated by determining the malondialdehyde concentration by HPLC. Sleep deprivation (SD) was used as an experimental approach to model the manic phase of BD. Results obtained from the kidney were compared to those obtained from erythrocytes and different brain regions in the same tested animals. Whereas treatment with therapeutic Li concentration did not bring any LP damage nor significant changes of Na/K-ATPase expression and [H]ouabain binding in the kidney, it conferred strong protection against this type of damage in the forebrain cortex. Importantly, the observed changes in erythrocytes indicated changes in forebrain cortices. Thus, different resistance to SD-induced changes of LP and Na/K-ATPase was detected in the kidney, erythrocytes and the brain of Li-treated rats. Our study revealed the tissue-specific protective properties of Li against LP and Na/K-ATPase regulation.
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http://dx.doi.org/10.1007/s00210-020-02036-4DOI Listing
May 2021

Differentiating mania/hypomania from happiness using a machine learning analytic approach.

J Affect Disord 2021 02 30;281:505-509. Epub 2020 Dec 30.

School of Psychiatry, University of New South Wales, Sydney, Australia; Black Dog Institute, Sydney, Australia.

Background: This study aimed to improve the accuracy of bipolar disorder diagnoses by identifying symptoms that help to distinguish mania/hypomania in bipolar disorders from general 'happiness' in those with unipolar depression.

Methods: An international sample of 165 bipolar and 29 unipolar depression patients (as diagnosed by their clinician) were recruited. All participants were required to rate a set of 96 symptoms with regards to whether they typified their experiences of manic/hypomanic states (for bipolar patients) or when they were 'happy' (unipolar patients). A machine learning paradigm (prediction rule ensembles; PREs) was used to derive rule ensembles that identified which of the 94 non-psychotic symptoms and their combinations best predicted clinically-allocated diagnoses.

Results: The PREs were highly accurate at predicting clinician bipolar and unipolar diagnoses (92% and 91% respectively). A total of 20 items were identified from the analyses, which were all highly discriminating across the two conditions. When compared to a classificatory approach insensitive to the weightings of the items, the ensembles were of comparable accuracy in their discriminatory capacity despite the unbalanced sample. This illustrates the potential for PREs to supersede traditional classificatory approaches.

Limitations: There were considerably less unipolar than bipolar patients in the sample, which limited the overall accuracy of the PREs.

Conclusions: The consideration of symptoms outlined in this study should assist clinicians in distinguishing between bipolar and unipolar disorders. Future research will seek to further refine and validate these symptoms in a larger and more balanced sample.
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http://dx.doi.org/10.1016/j.jad.2020.12.058DOI Listing
February 2021

Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions.

Entropy (Basel) 2020 Aug 1;22(8). Epub 2020 Aug 1.

Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada.

A system's heterogeneity () is the effective size of its event space, and can be quantified using the Rényi family of indices (also known as Hill numbers in ecology or Hannah-Kay indices in economics), which are indexed by an elasticity parameter q≥0. Under these indices, the heterogeneity of a composite system (the γ-heterogeneity) is decomposable into heterogeneity arising from variation and component subsystems (the α- and β-heterogeneity, respectively). Since the average heterogeneity of a component subsystem should not be greater than that of the pooled system, we require that γ≥α. There exists a multiplicative decomposition for Rényi heterogeneity of composite systems with discrete event spaces, but less attention has been paid to decomposition in the continuous setting. We therefore describe multiplicative decomposition of the Rényi heterogeneity for continuous mixture distributions under parametric and non-parametric pooling assumptions. Under non-parametric pooling, the γ-heterogeneity must often be estimated numerically, but the multiplicative decomposition holds such that γ≥α for q>0. Conversely, under parametric pooling, γ-heterogeneity can be computed efficiently in closed-form, but the γ≥α condition holds reliably only at q=1. Our findings will further contribute to heterogeneity measurement in continuous systems.
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http://dx.doi.org/10.3390/e22080858DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517460PMC
August 2020

Representational Rényi Heterogeneity.

Entropy (Basel) 2020 Apr 7;22(4). Epub 2020 Apr 7.

Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada.

A discrete system's heterogeneity is measured by the Rényi heterogeneity family of indices (also known as Hill numbers or Hannah-Kay indices), whose units are the numbers equivalent. Unfortunately, numbers equivalent heterogeneity measures for non-categorical data require a priori (A) categorical partitioning and (B) pairwise distance measurement on the observable data space, thereby precluding application to problems with ill-defined categories or where semantically relevant features must be learned as abstractions from some data. We thus introduce representational Rényi heterogeneity (RRH), which transforms an observable domain onto a latent space upon which the Rényi heterogeneity is both tractable and semantically relevant. This method requires neither a priori binning nor definition of a distance function on the observable space. We show that RRH can generalize existing biodiversity and economic equality indices. Compared with existing indices on a beta-mixture distribution, we show that RRH responds more appropriately to changes in mixture component separation and weighting. Finally, we demonstrate the measurement of RRH in a set of natural images, with respect to abstract representations learned by a deep neural network. The RRH approach will further enable heterogeneity measurement in disciplines whose data do not easily conform to the assumptions of existing indices.
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http://dx.doi.org/10.3390/e22040417DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516893PMC
April 2020

Genetic counselling for the prevention of mental health consequences of cannabis use: A randomized controlled trial-within-cohort.

Early Interv Psychiatry 2021 Oct 26;15(5):1306-1314. Epub 2020 Nov 26.

Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.

Background: Cannabis use is a risk factor for severe mental illness. However, cannabis does not affect everyone equally. Genetic information may help identify individuals who are more vulnerable to the harmful effects of cannabis on mental health. A common genetic variant within the AKT1 gene selectively increases risk of psychosis, only among those who use cannabis. Therapeutically oriented genetic counselling may enable us to reduce cannabis exposure among genetically sensitive individuals.

Methods: Using a trial-within-cohort design, we aim to test if genetic counselling, including the option to receive AKT1 rs2494732 genotype, reduces cannabis use. To this end, we have designed a genetic counselling intervention: Interdisciplinary approach to Maximize Adolescent potential: Genetic counselling Intervention to reduce Negative Environmental effects (IMAGINE).

Results: IMAGINE will be implemented in a cohort of children and youth enriched for familial risk for major mood and psychotic disorders. Approximately 110 eligible individuals aged 12-21 years will be randomized in a 1:1 ratio to be offered a single genetic counselling session with a board-certified genetic counsellor, or not. Allocated youth will also be invited to attend a follow-up session approximately 1 month following the intervention. The primary outcome will be cannabis use (measured by self-report or urine screen) at subsequent annual assessments as part of the larger cohort study. Secondary outcomes include intervention acceptability and psychopathology.

Conclusion: This study represents the first translational application of a gene-environment interaction to improve mental health and test an intervention with potential public health benefits. This study is registered with clinicaltrials.gov (NCT03601026).
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http://dx.doi.org/10.1111/eip.13082DOI Listing
October 2021

Association between Adherence with an Atypical Antipsychotic and with Other Psychiatric Drugs in Patients with Bipolar Disorder.

Pharmacopsychiatry 2021 Mar 17;54(2):75-80. Epub 2020 Nov 17.

Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA.

Background: Using U.S. pharmacy and medical claims, medication adherence patterns of patients with serious mental illness suggest that adherence to atypical antipsychotics may be related to adherence to other prescription drugs. This study investigated whether adherence to an atypical antipsychotic was related to adherence to other prescribed psychiatric drugs using self-reported data from patients with bipolar disorder.

Methods: Daily self-reported medication data were available from 123 patients with a diagnosis of bipolar disorder receiving treatment as usual who took at least 1 atypical antipsychotic over a 12-week period. Patients took a mean of 4.0±1.7 psychiatric drugs including the antipsychotic. The adherence rate for the atypical antipsychotic was compared to that for other psychiatric drugs to determine if the adherence rate for the atypical antipsychotic differed from that of the other psychiatric drug by at least ±10%.

Results: Of the 123 patients, 58 (47.2%) had an adherence rate for the atypical antipsychotic that differed from the adherence rate for at least 1 other psychiatric drug by at least±10%, and 65 (52.8%) patients had no difference in adherence rates. The patients with a difference took a larger total number of psychiatric drugs (p<0.001), had a larger daily pill burden (p=0.020) and a lower adherence rate with the atypical antipsychotic (p=0.007), and were more likely to take an antianxiety drug (p<0.001).

Conclusion: Adherence with an atypical antipsychotic was not useful for estimating adherence to other psychiatric drugs in about half of the patients with bipolar disorder.
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http://dx.doi.org/10.1055/a-1257-0813DOI Listing
March 2021

Measuring heterogeneity in normative models as the effective number of deviation patterns.

PLoS One 2020 13;15(11):e0242320. Epub 2020 Nov 13.

Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.

Normative modeling is an increasingly popular method for characterizing the ways in which clinical cohorts deviate from a reference population, with respect to one or more biological features. In this paper, we extend the normative modeling framework with an approach for measuring the amount of heterogeneity in a cohort. This heterogeneity measure is based on the Representational Rényi Heterogeneity method, which generalizes diversity measurement paradigms used across multiple scientific disciplines. We propose that heterogeneity in the normative modeling setting can be measured as the effective number of deviation patterns; that is, the effective number of coherent patterns by which a sample of data differ from a distribution of normative variation. We show that lower effective number of deviation patterns is associated with the presence of systematic differences from a (non-degenerate) normative distribution. This finding is shown to be consistent across (A) application of a Gaussian process model to synthetic and real-world neuroimaging data, and (B) application of a variational autoencoder to well-understood database of handwritten images.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242320PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665747PMC
January 2021

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

Hum Brain Mapp 2020 Oct 19. Epub 2020 Oct 19.

Department of Psychiatry, University of Münster, Münster, Germany.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
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http://dx.doi.org/10.1002/hbm.25249DOI Listing
October 2020

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Hum Brain Mapp 2020 Oct 7. Epub 2020 Oct 7.

Neuroscience Research Australia, Sydney, Australia.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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http://dx.doi.org/10.1002/hbm.25206DOI Listing
October 2020

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

JAMA Psychiatry 2021 Jan;78(1):47-63

Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht University, the Netherlands.

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

Design, Setting, And Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

Main Outcomes And Measures: Interregional profiles of group difference in cortical thickness between cases and controls.

Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

Conclusions And Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.2694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450410PMC
January 2021

The definition and measurement of heterogeneity.

Transl Psychiatry 2020 08 24;10(1):299. Epub 2020 Aug 24.

Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.

Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system's event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures-largely developed for economic and ecological research-to be useful in modern translational psychiatric science.
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http://dx.doi.org/10.1038/s41398-020-00986-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445182PMC
August 2020
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