The major aims of this project have been accomplished through the establishment of a large community-based family study of adult probands who participate in comprehensive clinical and biologic assessments followed by comparable evaluations of their adult and child relatives. Recruitment of probands and evaluation of relatives are near completion and analyses of the findings are underway. To date, about 575 probands and about 1100 of their relatives have completed the study, including over 150 children between the ages of 7-17. Approximately 500 individuals have also been evaluated at the NIH Clinical Center. Probands represent a large range of disorders including mood, anxiety, sleep, migraine, and cardiovascular in addition to controls. We are now completing interviews with relatives who had not previously participated in the study. During the past year, we have continued to recruit new probands and family members. We are also following up the original sample, repeating interviews, ecological momentary assessment (EMA), actigraphy, and clinic measures, so that we can assess the stability of these measures over time and track their relationship with emerging mental and medical illness in probands and family members, especially offspring. We have completed collection and genotyping of DNA samples obtained through the end of 2017, and began statistical genetic analyses. We have completed analyses of the clinical validity of our interview, the Diagnostic Interview for Affective and Anxiety Spectrum, as compared to the Structured Clinical Interview for DSM Disorders, and manuscript preparation is underway. We have conducted extensive analyses of the clinical and biomarker phenotypes of familial aggregation data during the past year. We tested the familial liability for Bipolar Disorder (BPD) using the Hypomania Checklist-32 (HCL-32), an instrument specifically developed to improve detection of cases of BPD that have a primarily depressed presentation. We found a 4-factor solution for the HCL-32, and demonstrated that is a valid tool to distinguish adults who have Bipolar I Disorder (BPI) or Bipolar II Disorder from those who have major depression or no mood disorders. We also found that the HCL Distractibility/Irritability factor was familial, suggesting that this factor may underlie the familial aggregation of BPD (Glaus et al, 2018). We have also devoted substantial effort to harmonize the measures and data sets from the Lausanne Family Study with the NIMH Family Study. We plan to conduct joint analyses of the data on youth in order to confirm findings from the Lausanne study and to increase the statistical power of these analyses. We have analyzed joint data on comorbidity and co-aggregation of suicide and mental disorders, and are now conducting joint analyses of the actigraphy data in order to evaluate associations between motor activity, sleep and mental health. We continue to complete analyses on additional biomarkers that were collected on both probands and relatives. We found BPI disorder was characterized by lower average and greater variability in motor activity, and that those with BPD have greater reactivity across homeostatic regulatory systems of activity, sleep, mood and energy (Shou et al, 2017). Analyses of olfactory thresholds and detection revealed that people with BPI and major depression have deficits in odor identification, particularly attributable to the subgroup with psychotic symptoms (Kamath et al, 2018). Several studies using ecological momentary sampling have been published in the last year. We further showed that people with BPD have greater reactivity to positive events, whereas variability in mood and anxiety appears to be a trait marker of people with a history of mood disorders in general (Lamers et al, in press). We also employed a novel statistical technique to study the stability of emotional and attention states using fragmentation models (Johns et al, in press). We have now developed new EMA scripts that will be used in several sites in order to increase the generalizability of the samples and the power of these analyses. We are also analyzing sleep patterns and disorders as well as physical activity and their associations with mood disorder subtypes. We also examined whether startle reactivity may comprise a marker of risk for anxiety disorders. We found that social anxiety is strongly associated with increased habituation and several measures of baseline startle and potentiated startle. These startle domains are also highly familial. Therefore, we plan to follow up these findings by extending the sample to include more people with Social Anxiety Disorder (SAD) and to recruit more family members. In summary, we have identified two familial subgroups that discriminate between subtypes of mood and anxiety disorders: (1) a group with BPI disorder that are characterized by circadian rhythm dysregulation in motor activity, sleep and mood, as well as greater cross-domain reactivity (Merikangas et al, in press); and (2) a group with SAD that tend to have greater reactivity to startle than those with mood disorders or controls, elevated familial risk of suicide attempts, and secondary mood disorders. The major shift in the emphasis of the study is to follow up the sample in order to evaluate the stability of the clinical phenomena and potential biomarkers and their association with developmental manifestations of mood disorders and their core components. Public Health Impact: Integration of the clinical, neuropsychological and psychophysiological measures within families will render an in-depth analysis of the biological mechanisms crucial for mood and anxiety disorders and their underlying diatheses. This will not only lead to a better understanding of these conditions and assist in identifying common genetic mechanisms, but may also lead to the development of novel treatment options and possible strategies for prevention and early intervention in those with elevated risk for these conditions. Future Plans: The initial findings of our study have major implications for etiology, treatment, course and nosology of mood and anxiety disorders. However, the work requires replication in larger samples, re-assessment to examine stability of the findings, and collaboration with other sites to cover the full range of the spectrum of mood disorders, and increase the power of the study. We are now working to complete enrollment of probands, particularly with BPD and SAD, and follow up the adult and child relatives, with a particular focus on youth ages 12-30. We are also continuing to collect DNA samples in relatives, complete telephone and online assessments that are now being developed and repeat the mobile technologies measures to test their generalizability across time, seasons and clinical state. Based on the findings from analyses of the study, we plan to design and pilot interventions that stabilize regulation of activity, sleep and other daily rhythms in this and other samples. We also plan to establish a collaborative network of affiliated studies of community, high risk and clinical samples of youth with common measures of mood and motor activity. We will also continue analysis of the comprehensive measures that have been collected in this study in the following domains: Clinical phenomenology, biologic and laboratory measures, genetic analysis, and development of statistical tools and analyses for the complex dynamic phenotypes derived from actigraphy and electronic diary measures. During the past few months, several of the key papers from these measures have been published or are in press. These analyses will also help us to identify subgroups in whom more intensive follow up will allow us to understand the key clinical and biological questions addressed by this protocol.