The chief goal of this study is to identify the endophenotypes of the spectrum of mood disorders using the methods of genetic epidemiology, developmental psychopathology and clinical psychiatry/psychology. The major research questions focus on the specificity of familial transmission of the mood disorder spectrum (i.e., symptoms, symptom clusters, subtypes) and the role of comorbidity with anxiety disorders and migraine syndromes in defining subtypes of mood disorders.? ? The phases of implementation of this research include: (1) development of measures of the spectrum of mood and anxiety disorders in adults and children, and structured interviews for the key components of the study phenotypes including mood, sleep and headache; (2) sampling and recruitment of probands from both clinical and community settings and enrollment and evaluation of the relatives; (3) selection and implementation of core features and endophenotypes for mood disorders and migraine; and (4) establishment of a high risk cohort to study the evolution of these disorders and the specificity of vulnerability markers and endophenotypes prior to clinical onset of these conditions.? (1) Measure development:? During the past year we have tested the measures that we developed during the past two years on 200 probands and 100 first degree relatives. We have conducted a validity study of the diagnostic interview that we developed, the Family Study Interview for Physical and Psychological Health compared to the SCID in 30 patients and the FSI detects all cases of mood disorders as well as a substantial number of other cases with subthreshold bipolar mood disorder. We have also now implemented the assessment of daily biologic rhythms and life experiences using Experience Sampling Method (ESM), a state-of-the-art ambulatory data collection technique that uses programmed electronic devices (e.g. palm micro-computers) to inform subjects of the exact moments to provide information concerning their behaviors, environments, and experiences. Under the direction of Joel Swendsen, Ph.D., a clinical psychologist and expert in ambulatory monitoring, data have recently been analyzed from a pilot of ESM in our samples that provided assessments of subjects four times each day over a 2-week period. Subject compliance with the methodology was remarkably high: 93% of all possible in vivo electronic interviews were completed (range 83% to 98%). Fatigue effects were negligible (missing data was equivalent for the last three days of the assessment period compared to the first three days), and subjects required only 3.3 minutes on average to complete each assessment. We have also used the Diagnostic Interview for Headache Syndrome (DIH) and the Sleep Patterns and Problems (SPP) Interview to obtain diagnostic information on sleep patterns and disorders and headache syndromes in the entire sample.? ? (2) Recruitment of probands and families? Sources of Probands: Clinical Settings: The two most fruitful sources for initial recruitment of clinical samples were the Behavioral Health Program at Suburban Hospital, which is immediately adjacent to the NIH campus, and the NIMH Clinical Research Center, that referred patients who had either been evaluated or treated in clinical protocols for mood disorders. To date, we have enrolled approximately 115 probands from these clinical settings. During the past few months, we have established an agreement with Children's National Medical Center to ascertain systematic samples of outpatients with headaches. ? ? Local Community Survey: In order to recruit an unbiased sample of probands and controls for our family study, we have conducted a survey of the local community. This sampling strategy enables us to reduce the bias inherent in clinic-based recruitment and other convenience methods such as advocacy groups, advertisements, newsletters, etc. The community sample will serve as a resource for selection of cases and controls for our current and future family studies of risk factors and/or disease spectra. The specific procedure that we have developed for recruitment has had overwhelming success in identifying probands and controls for our family study. The sampling frame is based on a large, commercially available list of verified home addresses from published telephone directory listings that fall within a 50 mile radius of the NIH campus in Bethesda We have used a random sampling procedure to select subsets of 500 names at a time. The procedure involves several mailings, a telephone screen for demographics and physical and mental health problems, and a random sampling of 20% of the non-respondents. Dr. Ronald Kessler, a survey sampling expert from Harvard University Department of Health Policy, has provided advice on establishing the methods for our community recruitment. To date, we have enrolled 242 participants into the study from the community. ? ? As of the date of this report, we have enrolled 459 probands and 287 relatives in the family study. ? ? (3) Phase III: Clinical Components and Endophenotypes? The aims of our future research are to further characterize and assess these clinical phenomena and to explore specific pathophysiologic pathways that may be involved in their manifestation. The specific domains tested address the two areas of complexity that remain impediments to replicable findings: core features of the phenotype and pathophysiologic trait markers. The following criteria were used to select measures: (1) components of the diagnostic criteria; (2) measures that have been shown to comprise potential trait markers for bipolar disorder, atypical depression, or migraine; (3) measures that have been demonstrated to be associated with bipolar disorder, atypical depression and migraine in prior studies; and (4) core features of these disorders that are associated with mood or anxiety disorders or migraine in our epidemiologic and family and high risk studies. The clinical measures that we are collecting include: biologic rhythms, white matter hyperintensities on 1.5 t MRIs, reproductive cycle in women, and prospective measures of diet, activity, life stress, and health. Potential trait markers include psychophysiologic measures, autonomic reactivity, sensory thresholds, and cardiovascular reactivity. ? To date, we have enrolled 58 probands and 15 relatives in the clinical component/endophenotype protocol. After we complete 25 probands per group, we plan to review and refine the measures. We will proceed to test affected and unaffected relatives on any of the measures that appear to discriminate between any of the affected proband groups and controls. Measures for the high risk youth will subsequently be developed on the basis of the findings for the probands and adult relatives. The study protocol provides greater detail on the measures, statistical methods and power analyses of the family study.? (4) Phase IV: High Risk Study of Offspring? We have begun to enroll children ages 8-17 in the high risk component of this study. We are conducting clinical psychiatric and neurologic evaluations of the children and then plan to conduct some of the laboratory studies that we are conducting in their parents.

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National Institute of Mental Health (NIMH)
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Shou, H; Cui, L; Hickie, I et al. (2017) Dysregulation of objectively assessed 24-hour motor activity patterns as a potential marker for bipolar I disorder: results of a community-based family study. Transl Psychiatry 7:e1211
Merikangas, K R; Zhang, J; Emsellem, H et al. (2014) The structured diagnostic interview for sleep patterns and disorders: rationale and initial evaluation. Sleep Med 15:530-5
Vande Voort, Jennifer L; He, Jian-Ping; Jameson, Nicole D et al. (2014) Impact of the DSM-5 attention-deficit/hyperactivity disorder age-of-onset criterion in the US adolescent population. J Am Acad Child Adolesc Psychiatry 53:736-44
Merikangas, K R; Cui, L; Heaton, L et al. (2014) Independence of familial transmission of mania and depression: results of the NIMH family study of affective spectrum disorders. Mol Psychiatry 19:214-9
Merikangas, Kathleen R (2013) Contributions of epidemiology to our understanding of migraine. Headache 53:230-46
Merikangas, Kathleen R; McClair, Vetisha L (2012) Epidemiology of substance use disorders. Hum Genet 131:779-89
Nyholt, Dale R; Gillespie, Nathan G; Merikangas, Kathleen R et al. (2009) Common genetic influences underlie comorbidity of migraine and endometriosis. Genet Epidemiol 33:105-13
Dierker, Lisa; He, Jianping; Kalaydjian, Amanda et al. (2008) The importance of timing of transitions for risk of regular smoking and nicotine dependence. Ann Behav Med 36:87-92
Vgontzas, Angeliki; Cui, Lihong; Merikangas, Kathleen R (2008) Are sleep difficulties associated with migraine attributable to anxiety and depression? Headache 48:1451-9
NCI-NHGRI Working Group on Replication in Association Studies; Chanock, Stephen J; Manolio, Teri et al. (2007) Replicating genotype-phenotype associations. Nature 447:655-60

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