**Section 9**

**Genetic Epidemiology Family-Based** 

376 Epidemiology Insights

Turvey, S.E., Bonilla, F.A., Junker, A.K. (2009). Primary immunodeficiency diseases: a

Verma, S., Sharma, P.K., Sivanandan, S., Rana, N., Saini, S., Lodha, R., Kabra, S.K. (2008).

Yavich, N., Báscolo, E.P., Hargerty, J. (2010). Bulding a PHC evaluation framework for Latin

Wang, L.L., Jin, Y.Y., Hao, Y.Q., Wang, J.J., Yao, C.M., Wang, X., Cao, R.M., Zhang. H., Chen.

Winkelstein, J.A., Marino, M.C., Lederman, H.M., Jones, S.M., Sullivan, K., Burks, A.W.,

Winkelstein, J.A., Marino, M.C., Ochs, H., Fuleihan, R., Scholl, P.R., Geha, R., Stiehm, E.R.,

Zegers, B.J., Weemaes, C.M., Weening, R.S., van der Meer, J.W., Vossen, J,M. (1994).

Zhao, H.J., Chen, T.X., Hao, Y.Q., Zhou, Y.F., Ying, D.M. (2006). Overview of clinical

*Geneeskunde*, Vol. 138 (February 1994), No. 7, pp. 354-9, ISSN 0028-2162. Zelazko, M., Carneiro-Sampaio, M., C., Cornejo de Luigi, M., Garcia de Olarte, D., Porras

*Immunology*, Vol. 31 (June 2011), No. 3, pp. 297-308, ISSN 1573-2592. Winkelstein, J.A., Marino, M.C., Johnston, R.B. Jr., Boyle, J., Curnutte, J., Gallin, J.I., Malech,

(Baltimore), Vol. 85 (July 2006), No. 4, pp. 193-202, ISSN 0025-7974.

*Pediatrics*, Vol. 75 (February 2008), No. 2, pp. 143-8, ISSN 0019-5456. Yarmohammadi, H., Estrella, L., Cunningham-Rundles, C. (2004). Diagnosis of Primary

2009), No. 1010, pp. 660-6, ISSN 0032-5473.

6749.

7974.

ISSN 0036-3634.

373-84, ISSN 0025-7974.

No. 2, pp. 161-6, ISSN 1573-2592.

6, ISSN 0412-3948.

practical guide for clinicians. *Postgraduated Medical Journal*, Vol. 85 (December

Spectrum of primary immune deficiency at a tertiary care hospital. *Indian Journal of* 

Immunodeficiency; Can Review of Medical History Help? *Journal of Allergy and Clinical Immunology*, Vol. 113 (February 2004), No. 2, Suppl. pp. s47, ISSN 0091-

America. *Salud Publica Mexico*, Vol. 52 (January-February 2010), No. 1, pp. 39-45,

Y., Chen, T.X. (2011). Distribution and clinical features of primary immunodeficiency diseases in chinese children (2004-2009). *Journal of Clinical* 

H.L., Holland, S.M., Ochs, H., Quie, P., Buckley, R.H., Foster, C.B., Chanock, S.J., Dickler, H. (2000). Chronic granulomatous disease. Report on a national registry of 368 patients. *Medicine* (Baltimore), Vol. 79 (May 2000), No. 3, pp.155-69, ISSN 0025-

Conley, M.E., Cunningham-Rundles, C., Ochs, H.D. (2006). X-linked agammaglobulinemia: report on a United States registry of 201 patients. *Medicine* 

Conley, M.E. (2003). The X-linked hyper-IgM syndrome: clinical and immunologic features of 79 patients. *Medicine* (Baltimore), Vol. 82 (November 2003), No. 6, pp.

Immunodeficiency in The Netherlands: clinical and immunological survey, 1970- 1983. Interfacultaire werkgroep Immunodeficiëntie. *Nederlands Tijdschrift voor* 

Madrigal, O., Berrón Perz, R., Cabello, A., Rostan, M.V., Sorensen, R.U. (1998). Primary immunodeficiency diseases in Latin America: first report from eight countries partipating in the LAGID. Latin American Group for Primary Immunodeficiency Diseases. *Journal of Clinical Immunology*, Vol. 18 (March 1998)

occurrence of primary immunodeficiency disorders in children. Zhonghua Er Bi Yan Hou Ke Za Zhi. *Chinese Journal of Pediatrics*, Vol. 44 (June 2006), No. 6, pp. 403-

**0**

**18**

Yun-Hee Choi

*Canada*

*University of Western Ontario*

**On Combining Family Data from Different**

**Associated with Mutated Genes**

**Study Designs for Estimating Disease Risk**

Genetic disorders caused primarily by abnormalities in genes or chromosomes are rare in the general population. The associated putative mutations that lead to a high risk of developing such diseases are even rarer. In order to study disease risks associated with mutated genes, families sampled under different study designs are commonly used in association studies. This is because family data recruited via affected individuals (probands) would be expected to contain more affected individuals and mutation carriers than families randomly sampled from a general population, thus leading to increased statistical efficiency in estimating the disease risk. The disease risk associated with a mutated gene can be measured on a relative or absolute scale. As the event we consider is disease with its age of onset, the relative risk can be measured as a ratio of two hazards of developing disease between mutation carriers and non-carriers, and the absolute risk as a function of age, i.e., the cumulative risk of developing

Several family-based study designs have been used for estimating the disease risk associated with a gene mutation when onset varies with age. Gong & Whittemore (2003) discussed two basic types of family-based sampling schemes: population-based and clinic-based designs. For population-based designs, families are ascertained for study inclusion based on affected family members who are randomly sampled from the disease population. The proband is usually genotyped to determine if s/he carries the disease risk gene and additional genotype and phenotype data can then be collected from other family members. A kin-cohort design described by Wacholder et al. (1998) is an example of the population-based design as families are sampled through a volunteer (either affected or unaffected) who agrees to be genotyped and provides the disease history of her or his first-degree relatives through a questionnaire. Not restricted to including the first degree relatives and genotyping only probands, a kin-cohort design can be easily extended to case-family studies to include more extended family members and their genotype information. Case-control family studies have been widely used to analyse the ages of onset of disease in relation to genetic risk (Li et al., 1998; Shih & Chatterjee, 2000; Hsu & Gorfine, 2006), where case families are recruited via population-based cases and their matching control families are randomly sampled from the

disease by a given age, which is also termed penetrance.

**1. Introduction**

population.
