Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.

BACKGROUND: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. METHODS: We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. RESULTS: We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. CONCLUSIONS: Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

The frequencies of mental disorders vary by geographic region. Investigating such variations may lead to more equitable access to mental healthcare and to scientific discoveries that reveal specific localized factors that contribute to the causes of mental illness. This study examined the frequency of three disorders with a major impact on public health ­ schizophrenia, bipolar disorder, and major depressive disorder ­ by analyzing electronic health records from a hospital providing comprehensive mental health care for a large region in Colombia. We show that individuals receiving outpatient care mainly live relatively near the facility. Those receiving inpatient care live throughout the region, but cluster in a few scattered locations. Future research could lead to strategies for more equitable provision of mental healthcare in Colombia and identify environmental or genetic factors that affect the likelihood that someone will develop one of these disorders.

Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia.

Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD. Analyzing EHR data from 13,607 patients diagnosed with MDD over 15 years, we identified 1,610 cases of conversion to BD. Using a multivariate Cox regression model, we identified severity of the initial MDD episode, the presence of psychosis and hospitalization at first episode, family history of mood or psychotic disorders, female gender to be predictive of the conversion to BD. Additionally, we observed associations with medication classes (prescriptions of mood stabilizers, antipsychotics, and antidepressants) and clinical features (delusions, suicide attempt, suicidal ideation, use of marijuana and alcohol use/abuse) derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within five years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%. Our study confirms many previously identified risk factors identified through registry-based studies (such as female gender and psychotic depression at the index MDD episode), and identifies novel ones (specifically, suicidal ideation and suicide attempt extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion as well as underscore its potential for the identification of novel risk factors and improving early diagnosis.

Distinct and shared contributions of diagnosis and symptom domains to cognitive performance in severe mental illness in the Paisa population: a case-control study.

BACKGROUND: Severe mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population. METHODS: In this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia). Participants were assessed for speed and accuracy using the Penn Computerized Neurocognitive Battery (CNB). Cases had structured interview-based diagnoses of schizophrenia, bipolar 1, bipolar 2, or major depressive disorder. Linear mixed models, using CNB tests as repeated measures, modelled neurocognition as a function of diagnosis, sex, and all interactions. Follow-up analyses in cases included symptom factor scores obtained from exploratory factor analysis of symptom data as main effects. FINDINGS: Between Oct 1, 2017, and Nov 1, 2019, 2406 participants (1689 cases [schizophrenia n=160; bipolar 1 disorder n=519; bipolar 2 disorder n=204; and major depressive disorder n=806] and 717 controls; mean age 39 years (SD 14); and 1533 female) were assessed. Participants with bipolar 1 disorder and schizophrenia had similar impairments in accuracy and speed across cognitive domains. Participants with bipolar 2 disorder and major depressive disorder performed similarly to controls, with subtle deficits in executive and social cognition. A three-factor model (psychosis, mania, and depression) best represented symptom data. Controlling for diagnosis, premorbid IQ, and disease severity, high lifetime psychosis scores were associated with reduced accuracy and speed across cognitive domains, whereas high depression scores were associated with increased social cognition accuracy. INTERPRETATION: Cross-diagnostic investigations showed that neurocognitive function in severe mental illness is characterised by two distinct profiles (bipolar 1 disorder and schizophrenia, and bipolar 2 disorder and major depressive disorder), and is associated with specific symptom domains. These results suggest the utility of this design for elucidating severe mental illness causes and trajectories. FUNDING: US National Institute of Mental Health.

Characterization of Expression Quantitative Trait Loci in Pedigrees from Colombia and Costa Rica Ascertained for Bipolar Disorder.

The observation that variants regulating gene expression (expression quantitative trait loci, eQTL) are at a high frequency among SNPs associated with complex traits has made the genome-wide characterization of gene expression an important tool in genetic mapping studies of such traits. As part of a study to identify genetic loci contributing to bipolar disorder and other quantitative traits in members of 26 pedigrees from Costa Rica and Colombia, we measured gene expression in lymphoblastoid cell lines derived from 786 pedigree members. The study design enabled us to comprehensively reconstruct the genetic regulatory network in these families, provide estimates of heritability, identify eQTL, evaluate missing heritability for the eQTL, and quantify the number of different alleles contributing to any given locus. In the eQTL analysis, we utilize a recently proposed hierarchical multiple testing strategy which controls error rates regarding the discovery of functional variants. Our results elucidate the heritability and regulation of gene expression in this unique Latin American study population and identify a set of regulatory SNPs which may be relevant in future investigations of complex disease in this population. Since our subjects belong to extended families, we are able to compare traditional kinship-based estimates with those from more recent methods that depend only on genotype information.

Genetic studies of neuropsychiatric disorders in Costa Rica: a model for the use of isolated populations.

The importance of genetics in understanding the etiology of mental illness has become increasingly clear in recent years, as more evidence has mounted that almost all neuropsychiatric disorders have a genetic component. It has also become clear, however, that these disorders are etiologically complex, and multiple genetic and environmental factors contribute to their makeup. So far, traditional linkage mapping studies have not definitively identified specific disease genes for neuropsychiatric disorders, although some potential candidates have been identified via these methods (e.g. the dysbindin gene in schizophrenia; Straub et al., 2002; Schwab et al., 2003). For this reason, alternative approaches are being attempted, including studies in genetically isolated populations. Because isolated populations have a high degree of genetic homogeneity, their use may simplify the process of identifying disease genes in disorders where multiple genes may play a role. Several areas of Latin America contain genetically isolated populations that are well suited for the study of neuropsychiatric disorders. Genetic studies of several major psychiatric illnesses, including bipolar disorder, major depression, schizophrenia, Tourette Syndrome, alcohol dependence, attention deficit hyperactivity disorder, and obsessive-compulsive disorder, are currently underway in these regions. In this paper we highlight the studies currently being conducted by our groups in the Central Valley of Costa Rica to illustrate the potential advantages of this population for genetic studies.

Genetic mapping using haplotype and model-free linkage analysis supports previous evidence for a locus predisposing to severe bipolar disorder at 5q31-33.

We report further evidence for our previous suggestion [Garner et al., 2001: Am J Hum Genet 68:1061-1064] of a locus on 5q predisposing to bipolar I disorder (BP-I) in an extended Costa Rican pedigree. We genotyped additional microsatellite markers in this region and applied a multi-point non-parametric linkage analysis (SimWalk2). Significant identity-by-descent allele sharing among affected relatives was observed for all of the 20 markers tested in a segment of approximately 15 cM. Most affected individuals shared a single haplotype over this region; breaks within this haplotype may suggest a more restricted candidate location for a BP-I gene. These results support the suggestion that a locus at 5q31-33, together with a previously reported locus at 18q22-23, may provide the major genetic risk for BP-I in this family.

Genomewide linkage disequilibrium mapping of severe bipolar disorder in a population isolate.

Genomewide association studies may offer the best promise for genetic mapping of complex traits. Such studies in outbred populations require very densely spaced single-nucleotide polymorphisms. In recently founded population isolates, however, extensive linkage disequilibrium (LD) may make these studies feasible with currently available sets of short tandem repeat markers, spaced at intervals as large as a few centimorgans. We report the results of a genomewide association study of severe bipolar disorder (BP-I), using patients from the isolated population of the central valley of Costa Rica. We observed LD with BP-I on several chromosomes; the most striking results were in proximal 8p, a region that has previously shown linkage to schizophrenia. This region could be important for severe psychiatric disorders, rather than for a specific phenotype.