Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group.

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

The lipidome in major depressive disorder: Shared genetic influence for ether-phosphatidylcholines, a plasma-based phenotype related to inflammation, and disease risk.

BACKGROUND: The lipidome is rapidly garnering interest in the field of psychiatry. Recent studies have implicated lipidomic changes across numerous psychiatric disorders. In particular, there is growing evidence that the concentrations of several classes of lipids are altered in those diagnosed with MDD. However, for lipidomic abnormalities to be considered potential treatment targets for MDD (rather than secondary manifestations of the disease), a shared etiology between lipid concentrations and MDD should be demonstrated. METHODS: In a sample of 567 individuals from 37 extended pedigrees (average size 13.57 people, range=3-80), we used mass spectrometry lipidomic measures to evaluate the genetic overlap between twenty-three biologically distinct lipid classes and a dimensional scale of MDD. RESULTS: We found that the lipid class with the largest endophenotype ranking value (ERV, a standardized parametric measure of pleiotropy) were ether-phosphodatidylcholines (alkylphosphatidylcholine, PC(O) and alkenylphosphatidylcholine, PC(P) subclasses). Furthermore, we examined the cluster structure of the twenty-five species within the top-ranked lipid class, and the relationship of those clusters with MDD. This analysis revealed that species containing arachidonic acid generally exhibited the greatest degree of genetic overlap with MDD. CONCLUSIONS: This study is the first to demonstrate a shared genetic etiology between MDD and ether-phosphatidylcholine species containing arachidonic acid, an omega-6 fatty acid that is a precursor to inflammatory mediators, such as prostaglandins. The study highlights the potential utility of the well-characterized linoleic/arachidonic acid inflammation pathway as a diagnostic marker and/or treatment target for MDD.

Genome-wide significant loci for addiction and anxiety.

BACKGROUND: Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. METHODS: Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. RESULTS: Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD=3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD=2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg=0.550-0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD=3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD=3.425). CONCLUSIONS: This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics.

Subcortical volumetric abnormalities in bipolar disorder.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Genome-wide autozygosity is associated with lower general cognitive ability.

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT).

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Shared genetic factors influence risk for bipolar disorder and alcohol use disorders.

Bipolar disorder and alcohol use disorder (AUD) have a high rate of comorbidity, more than 50% of individuals with bipolar disorder also receive a diagnosis of AUD in their lifetimes. Although both disorders are heritable, it is unclear if the same genetic factors mediate risk for bipolar disorder and AUD. We examined 733 Costa Rican individuals from 61 bipolar pedigrees. Based on a best estimate process, 32% of the sample met criteria for bipolar disorder, 17% had a lifetime AUD diagnosis, 32% met criteria for lifetime nicotine dependence, and 21% had an anxiety disorder. AUD, nicotine dependence and anxiety disorders were relatively more common among individuals with bipolar disorder than in their non-bipolar relatives. All illnesses were shown to be heritable and bipolar disorder was genetically correlated with AUD, nicotine dependence and anxiety disorders. The genetic correlation between bipolar and AUD remained when controlling for anxiety, suggesting that unique genetic factors influence the risk for comorbid bipolar and AUD independent of anxiety. Our findings provide evidence for shared genetic effects on bipolar disorder and AUD risk. Demonstrating that common genetic factors influence these independent diagnostic constructs could help to refine our diagnostic nosology.

Genome-Wide Analyses of Working-Memory Ability: A Review.

Working memory, a theoretical construct from the field of cognitive psychology, is crucial to everyday life. It refers to the ability to temporarily store and manipulate task-relevant information. The identification of genes for working memory might shed light on the molecular mechanisms of this important cognitive ability and-given the genetic overlap between, for example, schizophrenia risk and working-memory ability-might also reveal important candidate genes for psychiatric illness. A number of genome-wide searches for genes that influence working memory have been conducted in recent years. Interestingly, the results of those searches converge on the mediating role of neuronal excitability in working-memory performance, such that the role of each gene highlighted by genome-wide methods plays a part in ion channel formation and/or dopaminergic signaling in the brain, with either direct or indirect influence on dopamine levels in the prefrontal cortex. This result dovetails with animal models of working memory that highlight the role of dynamic network connectivity, as mediated by dopaminergic signaling, in the dorsolateral prefrontal cortex. Future work, which aims to characterize functional variants influencing working-memory ability, might choose to focus on those genes highlighted in the present review and also those networks in which the genes fall. Confirming gene associations and highlighting functional characterization of those associations might have implications for the understanding of normal variation in working-memory ability and also for the development of drugs for mental illness.

Transcriptomics of cortical gray matter thickness decline during normal aging.

INTRODUCTION: We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging. METHODS: Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 µm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability. RESULTS: Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT. CONCLUSION: Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.

Relationship between fractional anisotropy of cerebral white matter and metabolite concentrations measured using (1)H magnetic resonance spectroscopy in healthy adults.

Fractional anisotropy (FA) of water diffusion in cerebral white matter (WM), derived from diffusion tensor imaging (DTI), is a sensitive index of microscopic WM integrity. Physiological and metabolic factors that explain intersubject variability in FA values were evaluated in two cohorts of healthy adults of different age spans (N=65, range: 28-50years; and N=25, age=66.6±6.2, range: 57-80years). Single voxel magnetic resonance spectroscopy (MRS) was used to measure N-acetylaspartate (NAA), total choline-containing compounds, and total creatine, bilaterally in an associative WM tract: anterior corona radiata (ACR). FA values were calculated for the underlying, proximal and two distal WM regions. Two-stage regression analysis was used to calculate the proportion of variability in FA values explained by spectroscopy measurements, at the first stage, and subject's age, at the second stage. WM NAA concentration explained 23% and 66% of intersubject variability (p<0.001) in the FA of the underlying WM in the younger and older cohorts, respectively. WM NAA concentration also explained a significant proportion of variability in FA of the genu of corpus callosum (CC), a proximal WM tract where some of the fibers contained within the spectroscopic voxel decussate. NAA concentrations also explained a significant proportion of variability in the FA values in the splenium of CC, a distal WM tract that also carries associative fibers, in both cohorts. These results suggest that MRS measurements explained a significant proportion of variability in FA values in both proximal and distal WM tracts that carry similar fiber-types.

Event-related potential examination of facial affect processing in bipolar disorder and schizophrenia.

BACKGROUND: Patients with bipolar disorder exhibit consistent deficits in facial affect identification at both behavioral and neural levels. However, little is known about which stages of facial affect processing are dysfunctional. METHOD: Event-related potentials (ERPs), including amplitude and latency, were used to evaluate two stages of facial affect processing: N170 to examine structural encoding of facial features and N250 to examine decoding of facial features in 57 bipolar disorder patients, 30 schizophrenia patients and 30 healthy controls. Three conditions were administered: participants were asked to identify the emotion of a face, the gender of a face, or whether a building was one or two stories tall. RESULTS: Schizophrenia patients' emotion identification accuracy was lower than that of bipolar patients and healthy controls. N170 amplitude was significantly smaller in schizophrenia patients compared to bipolar patients and healthy controls, which did not differ from each other. Both patient groups had significantly longer N170 latency compared to healthy controls. For N250, both patient groups showed significantly smaller amplitudes compared with controls, but did not differ from each other. Bipolar patients showed longer N250 latency than healthy controls; patient groups did not differ from each other. CONCLUSIONS: Bipolar disorder patients have relatively intact structural encoding of faces (N170) but are impaired when decoding facial features for complex judgments about faces (N250 latency and amplitude), such as identifying emotion or gender.

Neurocognitive phenomics: examining the genetic basis of cognitive abilities.

Cognitive deficits are core to the disability associated with many psychiatric disorders. Both variation in cognition and psychiatric risk show substantial heritability, with overlapping genetic variants contributing to both. Unsurprisingly, therefore, these fields have been mutually beneficial : just as cognitive studies of psychiatric risk variants may identify genes involved in cognition, so too can genome-wide studies based on cognitive phenotypes lead to genes relevant to psychiatric aetiology. The purpose of this review is to consider the main issues involved in the phenotypic characterization of cognition, and to describe the challenges associated with the transition to genomewide approaches. We conclude by describing the approaches currently being taken by the international consortia involving many investigators in the field internationally (e.g. Cognitive Genomics Consortium; COGENT) to overcome these challenges.

Cross-cultural standardization of the South Texas Assessment of Neurocognition in India.

BACKGROUND & OBJECTIVES: Despite the central role of cognition for mental disorders most studies have been conducted in western countries. Similar research from other parts of the world, particularly India, is very limited. As a first step in closing this gap this cross-cultural comparability study of the South Texas Assessment of Neurocognition (STAN) battery was conducted between USA and India. METHODS: One hundred healthy adults from Kerala, India, were administered six language independent subtests of the Java Neuropsychological Test (JANET) version of the STAN, assessing aspects of general intellectual ability (Matrix Reasoning), attention (Identical Pairs Continuous Performance, 3 Symbol Version Test; IPCPTS), working memory (Spatial Capacity Delayed Response Test; SCAP), response inhibition (Stop Signal Reaction Time; SSRT), Emotional Recognition and Risk taking (Balloon Analogue Risk Task; BART). Test results were compared to a demographically matched US sample. RESULTS: Overall test performance in the Kerala sample was comparable to that of the US sample and commensurate to that generally described in studies from western countries. INTERPRETATION & CONCLUSIONS: Our results support the metric equivalence of currently available cognitive test batteries developed in western countries for use in India. However, the sample was restricted to individuals who were literate and had completed basic primary and secondary education.

The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI.

Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to bipolar disorder (BD) where disease risk is determined by the summation of many alleles of small individual magnitude. Modelling polygenic risk scores may be a powerful way of identifying disrupted brain regions whose genetic architecture is related to that of BD. We determined the extent to which common genetic variation underlying risk to BD affected neural activation during an executive processing/language task in individuals at familial risk of BD and healthy controls. Polygenic risk scores were calculated for each individual based on GWAS data from the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) of over 16 000 subjects. The familial group had a significantly higher polygene score than the control group (P=0.04). There were no significant group by polygene interaction effects in terms of association with brain activation. However, we did find that an increasing polygenic risk allele load for BD was associated with increased activation in limbic regions previously implicated in BD, including the anterior cingulate cortex and amygdala, across both groups. The findings suggest that this novel polygenic approach to examine brain-imaging data may be a useful means of identifying genetically mediated traits mechanistically linked to the aetiology of BD.

P-selectin Expression Tracks Cerebral Atrophy in Mexican-Americans.

BACKGROUND AND PURPOSE: We hypothesized that the P-selectin (SELP) gene, localized to a region on chromosome 1q24, pleiotropically contributes to increased blood pressure and cerebral atrophy. We tested this hypothesis by performing genetic correlation analyses for 13 mRNA gene expression measures from P-selectin and 11 other genes located in 1q24 region and three magnetic resonance imaging derived indices of cerebral integrity. METHODS: The subject pool consisted of 369 (219F; aged 28-85, average = 47.1 ± 12.7 years) normally aging, community-dwelling members of large extended Mexican-American families. Genetic correlation analysis decomposed phenotypic correlation coefficients into genetic and environmental components among 13 leukocyte-based mRNA gene expressions and three whole-brain and regional measurements of cerebral integrity: cortical gray matter thickness, fractional anisotropy of cerebral white matter, and the volume of hyperintensive WM lesions. RESULTS: From the 13 gene expressions, significant phenotypic correlations were only found for the P- and L-selectin expression levels. Increases in P-selectin expression levels tracked with decline in cerebral integrity while the opposite trend was observed for L-selectin expression. The correlations for the P-selectin expression were driven by shared genetic factors, while the correlations with L-selectin expression were due to shared environmental effects. CONCLUSION: This study demonstrated that P-selectin expression shared a significant variance with measurements of cerebral integrity and posits elevated P-selectin expression levels as a potential risk factor of hypertension-related cerebral atrophy.

Fractional anisotropy of water diffusion in cerebral white matter across the lifespan.

Determining the time of peak of cerebral maturation is vital for our understanding of when cerebral maturation ceases and the cerebral degeneration in healthy aging begins. We carefully mapped changes in fractional anisotropy (FA) of water diffusion for eleven major cerebral white matter tracts in a large group (831) of healthy human subjects aged 11-90. FA is a neuroimaging index of micro-structural white matter integrity, sensitive to age-related changes in cerebral myelin levels, measured using diffusion tensor imaging. The average FA values of cerebral white matter (WM) reached peak at the age 32 ± 6 years. FA measurements for all but one major cortical white matter tract (cortico-spinal) reached peaks between 23 and 39 years of age. The maturation rates, prior to age-of-peak were significantly correlated (r=0.74; p=0.01) with the rates of decline, past age-of-peak. Regional analysis of corpus callosum (CC) showed that thinly-myelinated, densely packed fibers in the genu, that connect pre-frontal areas, maturated later and showed higher decline in aging than the more thickly myelinated motor and sensory areas in the body and splenium of CC. Our findings can be summarized as: associative, cerebral WM tracts that reach their peak FA values later in life also show progressively higher age-related decline than earlier maturing motor and sensory tracts. These findings carry multiple and diverse implications for both theoretical studies of the neurobiology of maturation and aging and for the clinical studies of neuropsychiatric disorders.

Fractional anisotropy of cerebral white matter and thickness of cortical gray matter across the lifespan.

We examined age trajectories of fractional anisotropy (FA) of cerebral white matter (WM) and thickness of cortical gray matter (GM) in 1031 healthy human subjects (aged 11-90 years). Whole-brain FA and GM thickness values followed quadratic trajectories with age but the relationship between them was linear, indicating that a putative biological mechanism may explain the non-linearity of their age trajectories. Inclusion of the FA values into the quadratic model of the whole-brain and regional GM thickness changes with age made the effect of the age(2) term no longer significant for the whole-brain GM thickness and greatly reduced its significance for regional GM thickness measurements. The phylogenetic order of cerebral myelination helped to further explain the intersubject variability in GM thickness. FA values for the early maturing WM were significantly better (p=10(-6)) at explaining variability in GM thickness in maturing (aged 11-20) subjects than FA values for the late maturing WM. The opposite trend was observed for aging subjects (aged 40-90) where FA values for the late maturing WM were better (p=10(-16)) at explaining the variability in GM thickness. We concluded that the non-linearity of the age trajectory for GM thickness, measured from T1-weighted MRI, was partially explained by the heterogeneity and the heterochronicity of the age-related changes in the microintegrity of cerebral WM. We consider these findings as the evidence that the measurements of age-related changes in GM thickness and FA are driven, in part, by a common biological mechanism, presumed to be related to changes in cerebral myelination.

Common genetic influences on depression, alcohol, and substance use disorders in Mexican-American families.

Multiple genetic and environmental factors influence the risk for both major depression and alcohol/substance use disorders. In addition, there is evidence that these illnesses share genetic factors. Although, the heritability of these illnesses is well established, relatively few studies have focused on ethnic minority populations. Here, we document the prevalence, heritability, and genetic correlations between major depression and alcohol and drug disorders in a large, community-ascertained sample of Mexican-American families. A total of 1,122 Mexican-American individuals from 71 extended pedigrees participated in the study. All subjects received in-person psychiatric interviews. Heritability, genetic, and environmental correlations were estimated using SOLAR. Thirty-five percent of the sample met criteria for DSM-IV lifetime major depression, 34% met lifetime criteria for alcohol use disorders, and 8% met criteria for lifetime drug use disorders. The heritability for major depression was estimated to be h(2) = 0.393 (P = 3.7 × 10(-6)). Heritability estimates were higher for recurrent depression (h(2) = 0.463, P = 4.0 × 10(-6)) and early onset depression (h(2) = 0.485, P = 8.5 × 10(-5)). While the genetic correlation between major depression and alcohol use disorders was significant (ρ(g) = 0.58, P = 7 × 10(-3)), the environmental correlation between these traits was not significant. Although, there is evidence for increased rates of depression and substance use in US-born individuals of Mexican ancestry, our findings indicate that genetic control over major depression and alcohol/substance use disorders in the Mexican-American population is similar to that reported in other populations.