Toward Constructing an Endophenotype Strategy for Bipolar Disorders

Mood and Anxiety Disorders Program, National Institute of Mental Health, Bethesda, Maryland, USA.
Biological Psychiatry (Impact Factor: 10.26). 08/2006; 60(2):93-105. DOI: 10.1016/j.biopsych.2005.11.006
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Research aimed at elucidating the underlying neurobiology and genetics of bipolar disorder, and factors associated with treatment response, have been limited by a heterogeneous clinical phenotype and lack of knowledge about its underlying diathesis. We used a survey of clinical, epidemiological, neurobiological, and genetic studies to select and evaluate candidate endophenotypes for bipolar disorder. Numerous findings regarding brain function, brain structure, and response to pharmacological challenge in bipolar patients and their relatives deserve further investigation. Candidate brain function endophenotypes include attention deficits, deficits in verbal learning and memory, cognitive deficits after tryptophan depletion, circadian rhythm instability, and dysmodulation of motivation and reward. We selected reduced anterior cingulate volume and early-onset white matter abnormalities as candidate brain structure endophenotypes. Symptom provocation endophenotypes might be based on bipolar patients' sensitivity to sleep deprivation, psychostimulants, and cholinergic drugs. Phenotypic heterogeneity is a major impediment to the elucidation of the neurobiology and genetics of bipolar disorder. We present a strategy constructed to improve the phenotypic definition of bipolar disorder by elucidating candidate endophenotypes. Studies to evaluate candidate endophenotypes with respect to specificity, heritability, temporal stability, and prevalence in unaffected relatives are encouraged.

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    • "In conclusion, this association study of ER in a sample of patients with BD identified four SNPs accounting for 24.5% of the variance of AIM score. These results are illustrative of the proposal that focusing on a quantitative phenotype of the disorder (here affect intensity), possibly involving a smaller number of genes with a higher effect size, might help reducing the underlying genetic heterogeneity, thus favoring the identification of susceptibility genes (Hasler et al., 2006; Schulze 2010; Schulze and McMahon 2004). Further studies are required to confirm the involvement of the candidate genes identified here in their involvement in the regulation of affective states. "
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    ABSTRACT: Background: Emotional reactivity has been proposed as a relevant intermediate phenotype of bipolar disorder (BD). Our goal was to identify genetic factors underlying emotional reactivity in a sample of bipolar patients. Methods: Affect intensity (a proxy measure of emotional reactivity) was measured in a sample of 281 euthymic patients meeting DSM-IV criteria for BD. We use a validated dimensional tool, the 40-item self-report Affect Intensity Measure scale developed by Larsen and Diener. Patients with BD were genotyped for 475. 740 SNPs (using Illumina HumanHap550 Beadchips or HumanHap610 Quad chip). Association was investigated with a general mixed regression model of the continuous trait against genotypes, including gender as covariate. Results: Four regions (1p31.3, 3q13.11, 11p15.1 and 11q14.4) with a p-value lower or equal to 5×10(-6) were identified. In these regions, the joint effect of the four variants accounted for 24.5% of the variance of AIM score. Epistasis analysis did not detect interaction between these variants. In the 11p15.1 region, the rs10766743 located in the intron of the NELL1 gene remained significant after correction for multiple testing (p=2×10(-7)). Conclusions: These findings illustrate that focusing on quantitative intermediate phenotypes can facilitate the identification of genetic susceptibility variants in BD.
    Journal of Affective Disorders 09/2015; 188:101-106. DOI:10.1016/j.jad.2015.08.037 · 3.38 Impact Factor
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    • "Due to this strong hereditability, first-degree relatives may share genetic underlying influences which can cause brain alterations without the manifestation of the disease. If these alterations are potentially involved in the pathophysiology of the disease, they are called endophenotypes (Gottesman and Gould, 2003; Hasler et al., 2006). One strategy to identify endophenotypes is to compare BD patients with their relatives and healthy controls. "
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    ABSTRACT: Bipolar disorder (BD) is highly heritable. First-degree relatives of BD patient have an increased risk to develop the disease. We investigated abnormalities in gray matter (GM) volumes in healthy first-degree relatives of BD patients to identify possible brain structural endophenotypes for the disorder. 3D T1-weighted magnetic resonance images were obtained from 25 DSM-IV BD type I patients, 23 unaffected relatives, and 27 healthy controls (HC). A voxel-based morphometry protocol was used to compare differences in GM volumes between groups. BD patients presented reduced GM volumes bilaterally in the thalamus compared with HC. Relatives presented no global or regional GM differences compared with HC. Our negative results do not support the role of GM volume abnormalities as endophenotypes for BD. Thalamic volume abnormalities may be associated the pathophysiology of the disease.
    Psychiatry Research: Neuroimaging 09/2015; DOI:10.1016/j.pscychresns.2015.09.005 · 2.42 Impact Factor
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    • "These links warrant detailed exploration in future studies – especially in combination with focused processing speed and attentional assessment – to ascertain the utility of these measures as markers of structural and functional integrity in a variety of clinical disorders in which white matter impairments are implicated, such as neurodegenerative and mood disorders (Sachdev et al. 2005; Assareh et al. 2011; Poletti et al. 2015). Including assessment in individuals with genetic risk, for example for mood disorder, will further inform the extent to which they can be considered endophenotypic markers (Hasler et al. 2006). Developing understanding of the relationship between specific cognitive processes and their structural and functional underpinnings has clear clinical implications, especially in the potential use of neurocognitive function in the stratification of mood disorders (Insel et al. 2010). "
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    ABSTRACT: Attentional impairment is a core cognitive feature of major depressive disorder (MDD) and bipolar disorder (BD). However, little is known of the characteristics of response time (RT) distributions from attentional tasks. This is crucial to furthering our understanding of the profile and extent of cognitive intra-individual variability (IIV) in mood disorders. A computerized sustained attention task was administered to 138 healthy controls and 158 patients with a mood disorder: 86 euthymic BD, 33 depressed BD and 39 medication-free MDD patients. Measures of IIV, including individual standard deviation (iSD) and coefficient of variation (CoV), were derived for each participant. Ex-Gaussian (and Vincentile) analyses were used to characterize the RT distributions into three components: mu and sigma (mean and standard deviation of the Gaussian portion of the distribution) and tau (the 'slow tail' of the distribution). Compared with healthy controls, iSD was increased significantly in all patient samples. Due to minimal changes in average RT, CoV was only increased significantly in BD depressed patients. Ex-Gaussian modelling indicated a significant increase in tau in euthymic BD [Cohen's d = 0.39, 95% confidence interval (CI) 0.09-0.69, p = 0.011], and both sigma (d = 0.57, 95% CI 0.07-1.05, p = 0.025) and tau (d = 1.14, 95% CI 0.60-1.64, p < 0.0001) in depressed BD. The mu parameter did not differ from controls. Increased cognitive variability may be a core feature of mood disorders. This is the first demonstration of differences in attentional RT distribution parameters between MDD and BD, and BD depression and euthymia. These data highlight the utility of applying measures of IIV to characterize neurocognitive variability and the great potential for future application.
    Psychological Medicine 06/2015; -1:1-13. DOI:10.1017/S0033291715000926 · 5.94 Impact Factor
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