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Social Psychiatry and Psychiatric Epidemiology

, Volume 52, Issue 8, pp 1041–1058 | Cite as

The Lausanne–Geneva cohort study of offspring of parents with mood disorders: methodology, findings, current sample characteristics, and perspectives

  • Caroline L. Vandeleur
  • Marie-Pierre F. Strippoli
  • Enrique Castelao
  • Mehdi Gholam-Rezaee
  • François Ferrero
  • Pierre Marquet
  • Jean-Michel Aubry
  • Martin Preisig
Study Protocols and Samples

Abstract

Purpose

Studies focusing on the offspring of affected parents utilize the well-established familial aggregation of mood disorders as a powerful tool for the identification of risk factors, early clinical manifestations, and prodromes of mood disorders in these offspring. The major goals of the Lausanne–Geneva mood cohort study are to: (1) assess the familial aggregation of bipolar and unipolar mood disorders; (2) prospectively identify risk factors for mood disorders as well as their early signs and prodromes; (3) identify their endophenotypes including cognitive features, alterations in brain structure, HPA-axis dysregulation, and abnormalities of the circadian rhythm of activity.

Methods

Probands with bipolar disorders, major depressive disorder, and controls with at least one child aged from 4 to 17.9 years at study intake, their offspring, as well as their spouses are invited to take part in follow-up assessments at predetermined ages of the offspring. Direct semi-structured diagnostic interviews have been used for all participants. Probands, spouses, and adult offspring also undergo neurocognitive testing, anthropomorphic measures and biochemical exams, structural Magnetic Resonance Imaging, as well as objective assessments of physical activity using accelerometers in combination with ecological momentary assessments.

Results

Currently, our study has up to seven follow-up assessments extending over a period of 20 years. There are 214 probands and 389 offspring with one direct interview before age 18 as well as a second assessment over follow-up. Data on 236 co-parents are also available from whom 55% have been directly interviewed. First publications support the specificity of the familial aggregation of BPD and the strong influence of an early onset of the parental BPD, which amplifies the risk of developing this disorder in offspring.

Conclusions

Information from clinical, biological, cognitive, and behavioral measures, based on contemporary knowledge, should further enhance our understanding of mood disorder psychopathology, its consequences, and underlying mechanisms.

Keywords

Familial aggregation Prospective study Offspring of bipolar and depressed parents Risk factors Endophenotypes 

Notes

Acknowledgements

The authors would like to express their gratitude to the participants and to the collaborators who contributed to the coordination of the study and the collection of data. Special thanks to Prof. Pierre-François Leyvraz, Dr. Nicolas Favarger, and Prof. Daniel Egloff from the Orthopedic Department in Lausanne, as well as to Prof. Pierre Hoffmeyer from the Orthopedic Department in Geneva for their help with the recruitment of the comparison participants of this study.

Compliance with ethical standards

Role of funding sources

This research was and is supported by five grants from the Swiss National Foundation (SNF: #3200-040677, #32003B-105969, and #32003B-118326 to F. Ferrero; #3200-049746 and #3200-061974 to M. Preisig), two grants for a national research project “The Synaptic Bases of Mental Diseases” (#125759 and #158776 to P. Magistretti) financed by the Swiss National Foundation, and a Grant from GlaxoSmithKline Clinical Genetics. The funders had no involvement in any aspect of this study.

Conflict of interest

The authors declare that they have no competing interests.

Ethical approval

The study protocols at the baseline and follow-up assessments were approved by the review board of the University Hospital of Lausanne and have, therefore, been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Informed consent

All participants gave written informed consent for their participation prior to the assessments and parents provided informed consent for the participation of their children younger than 18 years.

References

  1. 1.
    Weissman MM, Merikangas KR, John K, Wickramaratne P, Prusoff BA, Kidd KK (1986) Family-genetic studies of psychiatric disorders. Developing technologies. Arch Gen Psychiatry 4311:1104–1116CrossRefGoogle Scholar
  2. 2.
    Merikangas KR, Cui L, Heaton L, Nakamura E, Roca C, Ding J et al (2014) Independence of familial transmission of mania and depression: results of the NIMH family study of affective spectrum disorders. Mol Psychiatry 192:214–219. doi: 10.1038/mp.2013.116 CrossRefGoogle Scholar
  3. 3.
    Vandeleur CL, Merikangas KR, Strippoli MP, Castelao E, Preisig M (2014) Specificity of psychosis, mania and major depression in a contemporary family study. Mol Psychiatry 192:209–213. doi: 10.1038/mp.2013.132 CrossRefGoogle Scholar
  4. 4.
    Wilde A, Chan HN, Rahman B, Meiser B, Mitchell PB, Schofield PR et al (2014) A meta-analysis of the risk of major affective disorder in relatives of individuals affected by major depressive disorder or bipolar disorder. J Affect Disord 158:37–47. doi: 10.1016/j.jad.2014.01.014 PubMedCrossRefGoogle Scholar
  5. 5.
    Merikangas KR, Low NC (2004) The epidemiology of mood disorders. Curr Psychiatry Rep 66:411–421CrossRefGoogle Scholar
  6. 6.
    Avenevoli S, Merikangas KR (2006) Implications of high-risk family studies for prevention of depression. Am J Prev Med 316(Suppl 1):S126–S135. doi: 10.1016/j.amepre.2006.07.003 CrossRefGoogle Scholar
  7. 7.
    Rasic D, Hajek T, Alda M, Uher R (2014) Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: a meta-analysis of family high-risk studies. Schizophr Bull 401:28–38. doi: 10.1093/schbul/sbt114 CrossRefGoogle Scholar
  8. 8.
    Radke-Yarrow M, Nottelmann E, Martinez P, Fox MB, Belmont B (1992) Young children of affectively ill parents: a longitudinal study of psychosocial development. J Am Acad Child Adolesc Psychiatry 311:68–77CrossRefGoogle Scholar
  9. 9.
    Preisig M, Strippoli MP, Castelao E, Merikangas KR, Gholam-Rezaee M, Marquet P et al (2016) The specificity of the familial aggregation of early-onset bipolar disorder: A controlled 10-year follow-up study of offspring of parents with mood disorders. J Affect Disord 190:26–33. doi: 10.1016/j.jad.2015.10.005 PubMedCrossRefGoogle Scholar
  10. 10.
    Birmaher B, Axelson D, Monk K, Kalas C, Goldstein B, Hickey MB et al (2009) Lifetime psychiatric disorders in school-aged offspring of parents with bipolar disorder: the Pittsburgh Bipolar Offspring study. Arch Gen Psychiatry 663:287–296CrossRefGoogle Scholar
  11. 11.
    Axelson D, Goldstein B, Goldstein T, Monk K, Yu H, Hickey MB et al (2015) Diagnostic precursors to bipolar disorder in offspring of parents with bipolar disorder: a longitudinal study. Am J Psychiatry 1727:638–646. doi: 10.1176/appi.ajp.2014.14010035 CrossRefGoogle Scholar
  12. 12.
    Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Ustun TB (2007) Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry 204:359–364. doi: 10.1097/YCO.0b013e32816ebc8c CrossRefGoogle Scholar
  13. 13.
    Duffy A, Lewitzka U, Doucette S, Andreazza A, Grof P (2012) Biological indicators of illness risk in offspring of bipolar parents: targeting the hypothalamic-pituitary-adrenal axis and immune system. Early Interv Psychiatry 62:128–137. doi: 10.1111/j.1751-7893.2011.00323.x CrossRefGoogle Scholar
  14. 14.
    Weissman MM, Wickramaratne P, Gameroff MJ, Warner V, Pilowsky D, Kohad RG et al (2016) Offspring of depressed parents: 30 years later. Am J Psychiatry: appiajp201615101327. doi: 10.1176/appi.ajp.2016.15101327 Google Scholar
  15. 15.
    Weissman MM, Wickramaratne P, Nomura Y, Warner V, Verdeli H, Pilowsky DJ et al (2005) Families at high and low risk for depression: a 3-generation study. Arch Gen Psychiatry 621:29–36CrossRefGoogle Scholar
  16. 16.
    Biederman J, Petty CR, Hirshfeld-Becker DR, Henin A, Faraone SV, Fraire M et al (2007) Developmental trajectories of anxiety disorders in offspring at high risk for panic disorder and major depression. Psychiatry Res 1533:245–252CrossRefGoogle Scholar
  17. 17.
    Kilford EJ, Foulkes L, Potter R, Collishaw S, Thapar A, Rice F (2015) Affective bias and current, past and future adolescent depression: a familial high risk study. J Affect Disord 174:265–271. doi: 10.1016/j.jad.2014.11.046 PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Rice F, Sellers R, Hammerton G, Eyre O, Bevan-Jones R, Thapar AK et al (2017) Antecedents of new-onset major depressive disorder in children and adolescents at high familial risk. JAMA Psychiatry 742:153–160. doi: 10.1001/jamapsychiatry.2016.3140 CrossRefGoogle Scholar
  19. 19.
    Duffy A, Alda M, Hajek T, Sherry SB, Grof P (2010) Early stages in the development of bipolar disorder. J Affect Disord 1211-2:127–135. doi: 10.1016/j.jad.2009.05.022 CrossRefGoogle Scholar
  20. 20.
    Mesman E, Nolen WA, Reichart CG, Wals M, Hillegers MH (2013) The Dutch bipolar offspring study: 12-year follow-up. Am J Psychiatry 1705:542–549. doi: 10.1176/appi.ajp.2012.12030401 CrossRefGoogle Scholar
  21. 21.
    Egeland JA, Endicott J, Hostetter AM, Allen CR, Pauls DL, Shaw JA (2012) A 16-year prospective study of prodromal features prior to BPI onset in well Amish children. J Affect Disord 1421-3:186–192. doi: 10.1016/j.jad.2012.04.023 CrossRefGoogle Scholar
  22. 22.
    Duffy A, Horrocks J, Doucette S, Keown-Stoneman C, McCloskey S, Grof P (2014) The developmental trajectory of bipolar disorder. Br J Psychiatry 2042:122–128. doi: 10.1192/bjp.bp.113.126706 CrossRefGoogle Scholar
  23. 23.
    Hafeman DM, Merranko J, Axelson D, Goldstein BI, Goldstein T, Monk K et al (2016) Toward the definition of a bipolar prodrome: dimensional predictors of bipolar spectrum disorders in at-risk youths. Am J Psychiatry 1737:695–704. doi: 10.1176/appi.ajp.2015.15040414 CrossRefGoogle Scholar
  24. 24.
    McNamara RK, Nandagopal JJ, Strakowski SM, DelBello MP (2010) Preventative strategies for early-onset bipolar disorder: towards a clinical staging model. CNS Drugs 2412:983–996. doi: 10.2165/11539700-000000000-00000 CrossRefGoogle Scholar
  25. 25.
    Doucette S, Levy A, Flowerdew G, Horrocks J, Grof P, Ellenbogen M et al (2014) Early parent-child relationships and risk of mood disorder in a Canadian sample of offspring of a parent with bipolar disorder: findings from a 16-year prospective cohort study. Early Interv Psychiatry. doi: 10.1111/eip.12195 PubMedGoogle Scholar
  26. 26.
    Kemner SM, Mesman E, Nolen WA, Eijckemans MJ, Hillegers MH (2015) The role of life events and psychological factors in the onset of first and recurrent mood episodes in bipolar offspring: results from the Dutch Bipolar Offspring Study. Psychol Med 4512:2571–2581. doi: 10.1017/S0033291715000495 CrossRefGoogle Scholar
  27. 27.
    Hirshfeld-Becker DR, Micco JA, Henin A, Petty C, Faraone SV, Mazursky H et al (2012) Psychopathology in adolescent offspring of parents with panic disorder, major depression, or both: a 10-year follow-up. Am J Psychiatry 16911:1175–1184CrossRefGoogle Scholar
  28. 28.
    Mars B, Collishaw S, Smith D, Thapar A, Potter R, Sellers R et al (2012) Offspring of parents with recurrent depression: which features of parent depression index risk for offspring psychopathology? J Affect Disord 1361-2:44–53. doi: 10.1016/j.jad.2011.09.002 CrossRefGoogle Scholar
  29. 29.
    Havinga PJ, Boschloo L, Bloemen AJ, Nauta MH, de Vries SO, Penninx BW et al (2017) Doomed for disorder? high incidence of mood and anxiety disorders in offspring of depressed and anxious patients: a prospective cohort study. J Clin Psychiatry 781:e8–e17. doi: 10.4088/JCP.15m09936 CrossRefGoogle Scholar
  30. 30.
    Hunt J, Schwarz CM, Nye P, Frazier E (2016) Is there a bipolar prodrome among children and adolescents? Curr Psychiatry Rep 184:35. doi: 10.1007/s11920-016-0676-3 CrossRefGoogle Scholar
  31. 31.
    Berk M, Hallam KT, McGorry PD (2007) The potential utility of a staging model as a course specifier: a bipolar disorder perspective. J Affect Disord 1001-3:279–281. doi: 10.1016/j.jad.2007.03.007 CrossRefGoogle Scholar
  32. 32.
    Hauser M, Correll CU (2013) The significance of at-risk or prodromal symptoms for bipolar I disorder in children and adolescents. Can J Psychiatry 581:22–31CrossRefGoogle Scholar
  33. 33.
    Faedda GL, Serra G, Marangoni C, Salvatore P, Sani G, Vazquez GH et al (2014) Clinical risk factors for bipolar disorders: a systematic review of prospective studies. J Affect Disord 168:314–321. doi: 10.1016/j.jad.2014.07.013 PubMedCrossRefGoogle Scholar
  34. 34.
    Hetrick SE, Parker AG, Hickie IB, Purcell R, Yung AR, McGorry PD (2008) Early identification and intervention in depressive disorders: towards a clinical staging model. Psychother Psychosom 775:263–270. doi: 10.1159/000140085 CrossRefGoogle Scholar
  35. 35.
    Klein DN, Glenn CR, Kosty DB, Seeley JR, Rohde P, Lewinsohn PM (2013) Predictors of first lifetime onset of major depressive disorder in young adulthood. J Abnorm Psychol 1221:1–6. doi: 10.1037/a0029567 CrossRefGoogle Scholar
  36. 36.
    McGorry P, Keshavan M, Goldstone S, Amminger P, Allott K, Berk M et al (2014) Biomarkers and clinical staging in psychiatry. World. Psychiatry 133:211–223. doi: 10.1002/wps.20144 Google Scholar
  37. 37.
    Duffy A, Malhi GS, Grof P (2016) Do the trajectories of bipolar disorder and schizophrenia follow a universal staging model? Can J Psychiatry. doi: 10.1177/0706743716649189 PubMedGoogle Scholar
  38. 38.
    Muneer A (2016) Staging models in bipolar disorder: a systematic review of the literature. Clin Psychopharmacol Neurosci 142:117–130. doi: 10.9758/cpn.2016.14.2.117
  39. 39.
    Etain B, Lajnef M, Bellivier F, Mathieu F, Raust A, Cochet B et al (2012) Clinical expression of bipolar disorder type I as a function of age and polarity at onset: convergent findings in samples from France and the United States. J Clin Psychiatry 734:e561–e566. doi: 10.4088/JCP.10m06504 CrossRefGoogle Scholar
  40. 40.
    Geoffroy PA, Etain B, Scott J, Henry C, Jamain S, Leboyer M et al (2013) Reconsideration of bipolar disorder as a developmental disorder: Importance of the time of onset. J Physiol Paris 1074:278–285. doi: 10.1016/j.jphysparis.2013.03.006 CrossRefGoogle Scholar
  41. 41.
    Gottesman, II, Gould TD (2003) The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 1604:636–645Google Scholar
  42. 42.
    Glahn DC, Bearden CE, Niendam TA, Escamilla MA (2004) The feasibility of neuropsychological endophenotypes in the search for genes associated with bipolar affective disorder. Bipolar Disord 63:171–182. doi: 10.1111/j.1399-5618.2004.00113.x CrossRefGoogle Scholar
  43. 43.
    Hasler G, Drevets WC, Manji HK, Charney DS (2004) Discovering endophenotypes for major depression. Neuropsychopharmacology 2910:1765–1781. doi: 10.1038/sj.npp.1300506 CrossRefGoogle Scholar
  44. 44.
    Hasler G (2006) Evaluating endophenotypes for psychiatric disorders. Rev Bras Psiquiatr 282:91–92CrossRefGoogle Scholar
  45. 45.
    Frangou S, Haldane M, Roddy D, Kumari V (2005) Evidence for deficit in tasks of ventral, but not dorsal, prefrontal executive function as an endophenotypic marker for bipolar disorder. Biol Psychiatry 5810:838–839. doi: 10.1016/j.biopsych.2005.05.020 CrossRefGoogle Scholar
  46. 46.
    Klimes-Dougan B, Ronsaville D, Wiggs EA, Martinez PE (2006) Neuropsychological functioning in adolescent children of mothers with a history of bipolar or major depressive disorders. Biol Psychiatry 609:957–965. doi: 10.1016/j.biopsych.2006.03.031 CrossRefGoogle Scholar
  47. 47.
    Maziade M, Rouleau N, Merette C, Cellard C, Battaglia M, Marino C et al (2011) Verbal and visual memory impairments among young offspring and healthy adult relatives of patients with schizophrenia and bipolar disorder: selective generational patterns indicate different developmental trajectories. Schizophr Bull 376:1218–1228. doi: 10.1093/schbul/sbq026 CrossRefGoogle Scholar
  48. 48.
    Duffy A, Hajek T, Alda M, Grof P, Milin R, MacQueen G (2009) Neurocognitive functioning in the early stages of bipolar disorder: visual backward masking performance in high risk subjects. Eur Arch Psychiatry Clin Neurosci 2595:263–269. doi: 10.1007/s00406-008-0862-3 CrossRefGoogle Scholar
  49. 49.
    Dougherty LR, Tolep MR, Smith VC, Rose S (2013) Early exposure to parental depression and parenting: associations with young offspring’s stress physiology and oppositional behavior. J Abnorm Child Psychol 418:1299–1310. doi: 10.1007/s10802-013-9763-7 CrossRefGoogle Scholar
  50. 50.
    Foland-Ross LC, Kircanski K, Gotlib IH (2014) Coping with having a depressed mother: the role of stress and coping in hypothalamic-pituitary-adrenal axis dysfunction in girls at familial risk for major depression. Dev Psychopathol 264(Pt 2):1401–1409. doi: 10.1017/S0954579414001102 CrossRefGoogle Scholar
  51. 51.
    Versace A, Ladouceur CD, Romero S, Birmaher B, Axelson DA, Kupfer DJ et al (2010) Altered development of white matter in youth at high familial risk for bipolar disorder: a diffusion tensor imaging study. J Am Acad Child Adolesc Psychiatry 4912:1249–1259, 1259 e1241. doi: 10.1016/j.jaac.2010.09.007
  52. 52.
    Dubin MJ, Weissman MM, Xu D, Bansal R, Hao X, Liu J et al (2012) Identification of a circuit-based endophenotype for familial depression. Psychiatry Res 2013:175–181. doi: 10.1016/j.pscychresns.2011.11.007 CrossRefGoogle Scholar
  53. 53.
    Nery FG, Monkul ES, Lafer B (2013) Gray matter abnormalities as brain structural vulnerability factors for bipolar disorder: a review of neuroimaging studies of individuals at high genetic risk for bipolar disorder. Aust N Z J Psychiatry 4712:1124–1135. doi: 10.1177/0004867413496482 CrossRefGoogle Scholar
  54. 54.
    Rifkin-Graboi A, Bai J, Chen H, Hameed WB, Sim LW, Tint MT et al (2013) Prenatal maternal depression associates with microstructure of right amygdala in neonates at birth. Biol Psychiatry 7411:837–844. doi: 10.1016/j.biopsych.2013.06.019 CrossRefGoogle Scholar
  55. 55.
    Talati A, Weissman MM, Hamilton SP (2013) Using the high-risk family design to identify biomarkers for major depression. Philos Trans R Soc Lond B Biol Sci 3681615:20120129. doi: 10.1098/rstb.2012.0129 CrossRefGoogle Scholar
  56. 56.
    Bauer IE, Sanches M, Suchting R, Green CE, El Fangary NM, Zunta-Soares GB et al (2014) Amygdala enlargement in unaffected offspring of bipolar parents. J Psychiatr Res 59:200–205. doi: 10.1016/j.jpsychires.2014.08.023 PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Hajek T, Gunde E, Slaney C, Propper L, MacQueen G, Duffy A et al (2009) Amygdala and hippocampal volumes in relatives of patients with bipolar disorder: a high-risk study. Can J Psychiatry 5411:726–733CrossRefGoogle Scholar
  58. 58.
    Wijndaele K, Westgate K, Stephens SK, Blair SN, Bull FC, Chastin SF et al (2015) Utilization and Harmonization of Adult Accelerometry Data: review and expert consensus. Med Sci Sports Exerc 4710:2129–2139. doi: 10.1249/MSS.0000000000000661 CrossRefGoogle Scholar
  59. 59.
    Kanning MK, Ebner-Priemer UW, Schlicht WM (2013) How to investigate within-subject associations between physical activity and momentary affective states in everyday life: a position statement based on a literature overview. Front Psychol 4:187. doi: 10.3389/fpsyg.2013.00187
  60. 60.
    von Haaren B, Loeffler SN, Haertel S, Anastasopoulou P, Stumpp J, Hey S et al (2013) Characteristics of the activity-affect association in inactive people: an ambulatory assessment study in daily life. Front Psychol 4:163. doi: 10.3389/fpsyg.2013.00163
  61. 61.
    Dunton GF, Huh J, Leventhal AM, Riggs N, Hedeker D, Spruijt-Metz D et al (2014) Momentary assessment of affect, physical feeling states, and physical activity in children. Health Psychol 333:255–263. doi: 10.1037/a0032640 CrossRefGoogle Scholar
  62. 62.
    Reid KJ, Jaksa AA, Eisengart JB, Baron KG, Lu B, Kane P et al (2012) Systematic evaluation of Axis-I DSM diagnoses in delayed sleep phase disorder and evening-type circadian preference. Sleep Med 139:1171–1177. doi: 10.1016/j.sleep.2012.06.024 CrossRefGoogle Scholar
  63. 63.
    Robillard R, Hermens DF, Naismith SL, White D, Rogers NL, Ip TK et al (2015) Ambulatory sleep-wake patterns and variability in young people with emerging mental disorders. J Psychiatry Neurosci 401:28–37CrossRefGoogle Scholar
  64. 64.
    Olino TM, McMakin DL, Morgan JK, Silk JS, Birmaher B, Axelson DA et al (2014) Reduced reward anticipation in youth at high-risk for unipolar depression: a preliminary study. Dev Cogn Neurosci 8: 55–64. doi: 10.1016/j.dcn.2013.11.005
  65. 65.
    aan het Rot M, Hogenelst K, Schoevers RA (2012) Mood disorders in everyday life: a systematic review of experience sampling and ecological momentary assessment studies. Clin Psychol Rev 326:510–523. doi: 10.1016/j.cpr.2012.05.007 CrossRefGoogle Scholar
  66. 66.
    Nurnberger JI Jr, Blehar MC, Kaufmann CA, York-Cooler C, Simpson SG, Harkavy-Friedman J et al (1994) Diagnostic interview for genetic studies. Rationale, unique features, and training. NIMH Genetics Initiative. Arch Gen Psychiatry 5111:849–859 (discussion 863–844)CrossRefGoogle Scholar
  67. 67.
    Endicott J, Spitzer RL (1978) A diagnostic interview: the schedule for affective disorders and schizophrenia. Arch Gen Psychiatry 357:837–844CrossRefGoogle Scholar
  68. 68.
    Valla JP, Bergeron L, Berube H, Gaudet N, St-Georges M (1994) A structured pictorial questionnaire to assess DSM-III-R-based diagnoses in children (6–11 years): development, validity, and reliability. J Abnorm Child Psychol 224:403–423CrossRefGoogle Scholar
  69. 69.
    Andreasen NC, Endicott J, Spitzer RL, Winokur G (1977) The family history method using diagnostic criteria. Reliability and validity. Arch Gen Psychiatry 3410:1229–1235CrossRefGoogle Scholar
  70. 70.
    Ferreri M (1996) Questionnaire d’événements de vie de F. Amiel-Lebigre. In: Guelfi JD (ed) L’évaluation clinique standardisée en psychiatrie. Tome II. Editions Médicales Pierre Fabre: Boulogne, pp 627–632Google Scholar
  71. 71.
    Swearingen EM, Cohen LH (1985) Measurement of adolescents’ life events: the junior high life experiences survey. Am J Community Psychol 131:69–85CrossRefGoogle Scholar
  72. 72.
    Bernstein DP, Stein JA, Newcomb MD, Walker E, Pogge D, Ahluvalia T et al (2003) Development and validation of a brief screening version of the Childhood Trauma Questionnaire. Child Abuse Negl 272:169–190CrossRefGoogle Scholar
  73. 73.
    Spielberger CD, Gorsuch RL, Lushene RE (1970) Manual for the State-Trait Anxiety Inventory (Self Evaluation Questionnaire). Consulting Psychologists Press, Palo Alto CAGoogle Scholar
  74. 74.
    Spielberger CD (1993) Inventaire d’Anxiete Etat-Trait. Les Editions du Centre de Psychologie Appliquée, ParisGoogle Scholar
  75. 75.
    Reznick JS, Hegeman IM, Kaufman ER, Woods SW, Jacobs M (1992) Retrospective and concurrent self-report of behavioral inhibition and their relation to adult mental health. Dev Psychopathol 4:301–321CrossRefGoogle Scholar
  76. 76.
    Tercier D, Vandeleur C, Jeanprêtre N, Rothen S, Vidal S, Halfon O et al (2012) Parent–offspring similarity for childhood behavioral inhibition and associations between inhibition and parental care. Fam Sci. doi: 10.1080/19424620.2012.689492 Google Scholar
  77. 77.
    Lerner RM, Palermo M, Spiro A, Nesselrode JR (1982) Assessing the dimension of temperamental individuality across the life-span: the dimensions of temperament survey (DOTS). Child Dev 53:149–159CrossRefGoogle Scholar
  78. 78.
    Windle M, Lerner RM (1986) Reassessing the dimensions of temperament individually across the life span. The Revised Dimensions of Temperament Survey (DOTS-R). J Adolesc Res 1:213–230CrossRefGoogle Scholar
  79. 79.
    Eysenck HJ, Eysenck SBG (1975) Manual of the Eysenck Personality Questionnaire. Hodder and Stroughton, LondonGoogle Scholar
  80. 80.
    Eysenck HJ, Eysenck SBG, Gauquelin M, Gauquelin F, Pascal C, Pascal D (1980) La structure de la personnalité chet les français confrontée à celle des anglais, comparaison “cross-culturelle”. Personnalité 1–2:7–29Google Scholar
  81. 81.
    Rothen S, Vandeleur CL, Lustenberger Y, Jeanprêtre N, Ayer E, Sisbane F et al (2008) Validation of the French version of the EPQ-Junior. Personal Indiv Differ 44:464–474CrossRefGoogle Scholar
  82. 82.
    Parker G, Tupling H, Brown LB (1979) A parental bonding instrument. Br J Med Psychol 52:1–10CrossRefGoogle Scholar
  83. 83.
    Mohr S, Preisig M, Fenton BT, Ferrero F (1999) Validation of the French version of the parental bonding instrument in adults. Personal Indiv Differ 26:1065–1074CrossRefGoogle Scholar
  84. 84.
    Achenbach TM, Edelbrock CS (1983) Manual for the Child Behavior Checklist and the Revised Child Behavior Profile. University of Vermont, Burlington VTGoogle Scholar
  85. 85.
    Fombonne E (1989) The Child Behaviour Checklist and the Rutter Parental Questionnaire: a comparison between two screening instruments. Psychol Med 193:777–785CrossRefGoogle Scholar
  86. 86.
    Olson DH, Portner J, Lavee Y. FACES III. Family Social Science. University of Minnesota: St. Paul, 1985.Google Scholar
  87. 87.
    Vandeleur CL, Preisig M, Fenton BT, Ferrero F (1999) Validation of a French version of FACES-III in adolescents and adults. Swiss. J Psychol 58:161–169Google Scholar
  88. 88.
    Kavanaugh DJ, O’Halloran P, Manicavasagar V, Clark D, Piatkowska O, Tennant C et al (1997) The Family Attitude Scale: reliability and validity of a new scale for measuring the emotional climate of families. Psychiatr Res 70:185–195Google Scholar
  89. 89.
    Vandeleur CL, Kavanagh DJ, Favez N, Castelao E, Preisig M (2013) French version of the Family Attitude Scale: psychometric properties and relation of attitudes to the respondent’s psychiatric status. Psychiatry Res 2102:641–646. doi: 10.1016/j.psychres.2013.07.008 CrossRefGoogle Scholar
  90. 90.
    Bolognini M, Plancherel B, Halfon O (1998) Tracas quotidiens et santé à l’adolescence. Neuropsychiatrie de l’Enfance et de l’Adolescence 46:297–305Google Scholar
  91. 91.
    Spanier GB (1976) Measuring dyadic adjustment: new scales for assessing the quality of marriage and similar dyads. J Marriage Fam 38:15–28CrossRefGoogle Scholar
  92. 92.
    Vandeleur CL, Fenton BT, Ferrero F, Preisig M (2003) Construct Validity of the French Version of the Dyadic Adjustment Scale. Swiss. J Psychol 62:167–175Google Scholar
  93. 93.
    Grob A, Bodmer NM, Flammer A (1993) Living conditions in Europe: the case of Switzerland. University of Bern, Institute of Psychology, BernGoogle Scholar
  94. 94.
    Perrin M, Vandeleur CL, Castelao E, Rothen S, Glaus J, Vollenweider P et al (2014) Determinants of the development of post-traumatic stress disorder, in the general population. Soc Psychiatry Psychiatr Epidemiol 493:447–457. doi: 10.1007/s00127-013-0762-3 CrossRefGoogle Scholar
  95. 95.
    Petersen A, Crockett L, Tobin-Richards M, Boxer A (1985) Measuring pubertal status: Reliability and validity of a self-report measure. Pennsylvania State UniversityGoogle Scholar
  96. 96.
    Kochman F, Ferrari P, Hantouche E, Akiskal H (2002) Les troubles bipolaires chez l’adolescent. Actualités en psychiatrie de l’enfant et de l’adolescent. Flammarion, ParisGoogle Scholar
  97. 97.
    Leckman JF, Sholomskas D, Thompson WD, Belanger A, Weissman MM (1982) Best estimate of lifetime psychiatric diagnosis: a methodological study. Arch Gen Psychiatry 398:879–883CrossRefGoogle Scholar
  98. 98.
    Rougemont-Buecking A, Rothen S, Jeanpretre N, Lustenberger Y, Vandeleur CL, Ferrero F et al (2008) Inter-informant agreement on diagnoses and prevalence estimates of anxiety disorders: direct interview versus family history method. Psychiatry Res 1571-3:211–223. doi: 10.1016/j.psychres.2006.04.022 CrossRefGoogle Scholar
  99. 99.
    Vandeleur CL, Rothen S, Jeanpretre N, Lustenberger Y, Gamma F, Ayer E et al (2008) Inter-informant agreement and prevalence estimates for substance use disorders: direct interview versus family history method. Drug Alcohol Depend 921-3:9–19. doi: 10.1016/j.drugalcdep.2007.05.023 CrossRefGoogle Scholar
  100. 100.
    Vandeleur CL, Rothen S, Lustenberger Y, Glaus J, Castelao E, Preisig M (2015) Inter-informant agreement and prevalence estimates for mood syndromes: direct interview vs. family history method. J Affect Disord 171:120–127. doi: 10.1016/j.jad.2014.08.048 PubMedCrossRefGoogle Scholar
  101. 101.
    Leboyer M, Barbe B, Gorwood P, Teherani M, Allilaire JF, Preisig M et al (1995) Interview Diagnostique pour les Etudes Génétiques. INSERM, ParisGoogle Scholar
  102. 102.
    Preisig M, Fenton BT, Matthey ML, Berney A, Ferrero F (1999) Diagnostic interview for genetic studies (DIGS): inter-rater and test-retest reliability of the French version. European Archives of Psychiatry &amp. Clin Neurosci 2494:174–179Google Scholar
  103. 103.
    Berney A, Preisig M, Matthey ML, Ferrero F, Fenton BT (2002) Diagnostic interview for genetic studies (DIGS): inter-rater and test-retest reliability of alcohol and drug diagnoses. Drug Alcohol Depend 652:149–158Google Scholar
  104. 104.
    Leboyer M, Maier W, Teherani M, Lichtermann D, D’Amato T, Franke P et al (1991) The reliability of the SADS-LA in a family study setting. Eur Arch Psychiatry Clin Neurosci 2413:165–169CrossRefGoogle Scholar
  105. 105.
    Orvaschel H, Puig-Antich J, Chambers W, Tabrizi MA, Johnson R (1982) Retrospective assessment of prepubertal major depression with the Kiddie-SADS-E. J Am Acad Child Adolesc Psychiatry 214:392–397CrossRefGoogle Scholar
  106. 106.
    Vandeleur C, Rothen S, Gholam-Rezaee M, Castelao E, Vidal S, Favre S et al (2012) Mental disorders in offspring of parents with bipolar and major depressive disorders. Bipolar Disord 146:641–653. doi: 10.1111/j.1399-5618.2012.01048.x CrossRefGoogle Scholar
  107. 107.
    Chambers WJ, Puig-Antich J, Hirsch M, Paez P, Ambrosini PJ, Tabrizi MA et al (1985) The assessment of affective disorders in children and adolescents by semistructured interview. Test-retest reliability of the schedule for affective disorders and schizophrenia for school-age children, present episode version. Arch Gen Psychiatry 427:696–702CrossRefGoogle Scholar
  108. 108.
    Gammon GD, John K, Rothblum ED, Mullen K, Tischler GL, Weissman MM (1983) Use of a structured diagnostic interview to identify bipolar disorder in adolescent inpatients: frequency and manifestations of the disorder. Am J Psychiatry 1405:543–547Google Scholar
  109. 109.
    Rothen S, Vandeleur CL, Lustenberger Y, Jeanpretre N, Ayer E, Gamma F et al (2009) Parent-child agreement and prevalence estimates of diagnoses in childhood: direct interview versus family history method. Int J Methods Psychiatr Res 182:96–109CrossRefGoogle Scholar
  110. 110.
    Nuechterlein KH, Green MF, Kern RS, Baade LE, Barch DM, Cohen JD et al (2008) The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity. Am J Psychiatry 1652:203–213. doi: 10.1176/appi.ajp.2007.07010042 CrossRefGoogle Scholar
  111. 111.
    Van Rheenen TE, Rossell SL (2014) An empirical evaluation of the MATRICS consensus cognitive battery in bipolar disorder. Bipolar Disord 163:318–325. doi: 10.1111/bdi.12134 CrossRefGoogle Scholar
  112. 112.
    Yatham LN, Torres IJ, Malhi GS, Frangou S, Glahn DC, Bearden CE et al (2010) The international society for bipolar disorders-battery for assessment of neurocognition (ISBD-BANC). Bipolar Disord 124:351–363. doi: 10.1111/j.1399-5618.2010.00830.x CrossRefGoogle Scholar
  113. 113.
    Spreen O, Strauss E (1998) A compendium of neuropsychological tests: administration, norms, and commentary. Oxford University Press, OxfordGoogle Scholar
  114. 114.
    Roinishvili M, Chkonia E, Stroux A, Brand A, Herzog MH (2011) Combining vernier acuity and visual backward masking as a sensitive test for visual temporal deficits in aging research. Vision Res 514:417–423. doi: 10.1016/j.visres.2010.12.011 CrossRefGoogle Scholar
  115. 115.
    Freeman DJ (1984) Sample size determination in comparative studies. In: Bracken MB (ed) Perinatal epidemiology. Oxford University Press, New YorkGoogle Scholar
  116. 116.
    Fassassi S, Vandeleur C, Aubry JM, Castelao E, Preisig M (2014) Prevalence and correlates of DSM-5 bipolar and related disorders and hyperthymic personality in the community. J Affect Disord 167:198–205. doi: 10.1016/j.jad.2014.06.004 PubMedCrossRefGoogle Scholar
  117. 117.
    Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 626:593–602. doi: 10.1001/archpsyc.62.6.593 CrossRefGoogle Scholar
  118. 118.
    Rothen S, Vandeleur CL, Lustenberger Y, Jeanpretre N, Ayer E, Fornerod D et al (2009) Personality traits in children of parents with unipolar and bipolar mood disorders. J Affect Disord 1131-2:133–141. doi: 10.1016/j.jad.2008.05.013 CrossRefGoogle Scholar
  119. 119.
    Angst J, Gamma A, Benazzi F, Ajdacic V, Eich D, Rossler W (2003) Toward a re-definition of subthreshold bipolarity: epidemiology and proposed criteria for bipolar-II, minor bipolar disorders and hypomania. J Affect Disord 731-2:133–146CrossRefGoogle Scholar
  120. 120.
    Angst J, Merikangas KR, Preisig M (1997) Subthreshold syndromes of depression and anxiety in the community. J Clin Psychiatry 58(Suppl 8):6–10PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Caroline L. Vandeleur
    • 1
  • Marie-Pierre F. Strippoli
    • 1
  • Enrique Castelao
    • 1
  • Mehdi Gholam-Rezaee
    • 1
  • François Ferrero
    • 2
  • Pierre Marquet
    • 1
  • Jean-Michel Aubry
    • 2
  • Martin Preisig
    • 1
  1. 1.Department of PsychiatryUniversity Hospital of LausanneLausanneSwitzerland
  2. 2.Department of Mental Health and PsychiatryUniversity Hospital of GenevaGenevaSwitzerland

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