Pedigree and Population Resource (PPR) facilitates investigators' use and access of the Utah Population Database (UPDB) through Kinship Analysis Tools and other pedigree software. Highly specialized software has been developed to test for familial aggregation of disease, to estimate the magnitude of familial risks, and to identify families at high risk for a disease (Kerber 1995; Boucher and Kerber 2001; Kerber, O’Brien et al, 2001; Kerber and O’Brien 2005). Descriptive tools such as pedigree drawing, calculation of kinship coefficients, and ascending or descending pedigrees with generational information are available for project investigators. A brief description of the Kinship Analysis Tools are below.
Descriptive Tools for the UPDB
| KinshipCoefficient: | Pairs of individuals are provided and their ancestors are compared to identify a common ancestor. If one or more common ancestors are identified, a kinship coefficient is calculated to indicate the degree of relatedness. |
| Ascend: | Lists all ancestors by generation and ID number for an individual in the UPDB. Can indicate cancer status and names if approved. |
| Descend: | Lists all descendants by generation and ID number for an individual in the UPDB. Can indicate cancer status and names if approved. |
| Peddraw: | Provides all descendants for import into Progeny pedigree drawing program. |
Analytics Tools for UPDB
| Kinclass: | This program rapidly identifies arbitrary classes of relatives for a set of individuals according to a set of criteria, such as first- and second-degree relatives who are still alive. Used primarily for calculating recurrence risk estimates (e.g., relative risk of a disease recurring in siblings, cousins, children, etc.). |
| Dynaped: |
This program takes the output from a control dataset and a kinship dataset and performs various types of statistical analysis. The functionality of this program includes
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Kinclass Reports
This is an example of the output from Kinclass using statewide melanoma cancer data. There were 14970 cases used in this analysis. One control was selected and matched to each case by age and sex. Specific classes of relatives (first degree, second degree, first cousins, cousins once removed) of patients and controls were compared for the recurrence of melanoma. The relative risk of recurrence is estimated using both logistic and Cox regressions. P values and confidence intervals are also provided as measures of statistical significance. Using the large pedigree available in UPDB, one finds that there were 447 first degree relatives (parent/child or siblings) of cases with melanoma and 35,918 first degree relatives who did not have melanoma. For controls there were 189 first degree relatives of controls identified with melanoma and 34,001 who did not have melanoma. Thus first degree relatives of cases have a 2.2 fold increase in risk for melanoma. The risk is lower for more distant relatives but still signifigant; there was a 45% increased risk in second degree relatives, a 26% increased risk for first cousins (third degree), and 17% increased risk for cousins once removed.
Kerber R. (1995) "Method for calculating risk associated with family history of disease." Genet.Epidemiol. 12:291-301.
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Cases |
Controls |
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| Relationship | Affected | Unaffected | Affected | Unaffected |
| First degree | 447 | 35918 | 189 | 34001 |
| Second degree | 475 | 78151 | 305 | 72153 |
| First cousins | 901 | 99897 | 656 | 91824 |
| Once removed | 610 | 104867 | 527 | 105712 |
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Logistic Regression |
Cox Regression |
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| Relationship | Relative Risk | Confidence Interval | P Value | Relative Risk | Confidence Interval | P Value |
| First degree | 2.26 | 1.9 - 2.68 | <0.0001 | 2.24 | 1.85 - 2.73 | <0.0001 |
| Second degree | 1.45 | 1.25 - 1.67 | <0.0001 | 1.46 | 1.25 - 1.72 | <0.0001 |
| First cousins | 1.26 | 1.14 - 1.4 | <0.0001 | 1.26 | 1.12 - 1.41 | <0.0001 |
| Once removed | 1.17 | 1.04 - 1.31 | 0.0097 | 1.17 | 1.04 - 1.32 | <0.0001 |
Contact Us
Utah Population Database Director
Nicola Camp, PhD
nicola.camp@hci.utah.edu
Utah Population Database Operations Manager
Dinah Busico, MPA
Dinah.Busico@hci.utah.edu
Governance
HCI Senior Director Oversight
Tracy Onega, PhD, MS
Faculty Advisory Committee Chair
Jen Doherty, PhD, MS
Faculty Advisory Committee Members
Jahn Barlow, MPA
Diana Brixner, PhD
Caren Frost, PhD
Steven Guthery, MD
Barry Nangle, PhD
Brock O’Neil, MD
Andrew Post, MD, PhD
Katharine Ullman, PhD
Michael Varner, MD