Computer-assisted phenotype characterization for genetic research in psychiatry

Hum Hered. 2004;58(3-4):122-30. doi: 10.1159/000083538.


Psychiatric disorders differ from other complex phenotypes in their lack of objectively assessable biological markers that contribute to the establishment of a research diagnosis for genetic studies. To nevertheless allow for the delineation of genetically meaningful diagnostic entities for psychiatric genetic research, comprehensive phenotype characterization procedures are required. It is widely agreed that these should include the standardized assessment of life-time clinical symptomatology, sociodemographic, and environmental factors. Data should be based on several sources, i.e. diagnostic interviews with probands and their relatives as well as a thorough review of medical records, and final assignment of diagnosis should follow robust algorithms (i.e. best-estimate procedures, consensus diagnosis). Here, we outline a practical implementation of such a phenotype characterization strategy, including patient recruitment, study enrolment procedures, comprehensive diagnostic assessment, and data management. We argue that successful psychiatric phenotype characterization requires flexible tools. For this purpose, we have developed a computer-assisted phenotype characterization inventory, built around the backbone of a relational database. It allows for the straightforward assessment of symptoms, automated error checks and diagnostic assignment, easily manageable data storage and handling, and flexible data transfer between various research centers even across language barriers, while at the same time keeping up with the highest standards for the protection of sensitive patient data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Family Health
  • Genetic Markers
  • Humans
  • Mental Disorders / diagnosis*
  • Mental Disorders / genetics*
  • Phenotype*
  • Psychiatric Status Rating Scales
  • Psychiatry / methods*
  • Research Design
  • Software


  • Genetic Markers