Measuring familial aggregation by using odds‐ratio regression models

Liang, Kung Yee; Beaty, Terri

doi:10.1002/gepi.1370080602

Cited by 60 publications

(46 citation statements)

References 20 publications

(12 reference statements)

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“…The familial aggregation of the survival predictors' outcomes was thus measured according to Liang and Beaty (1991), using a regression model which incorporates effects of individual covariates. The odds ratios (ORs) or the β coefficients of specific survival predictors' outcomes estimated within sib-ships (the proband and his/her sib) were then compared with the same measures estimated within unrelated duos (the proband and a subject belonging to another sib-ship, matched to the real proband's sib for gender, year and place of birth and recruitment centre).…”

Section: Discussionmentioning

confidence: 99%

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Cevenini¹,

Cotichini²,

Stazi³

et al. 2013

AGE

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In a scenario of increasing life expectancy worldwide, it is mandatory to identify the characteristics of a healthy aging phenotype, including survival predictors, and to disentangle those related to environment/ lifestyle versus those related to familiarity/genetics. To this aim we comprehensively characterised a cohort of 1,160 Italian subjects of 90 years and over (90+, mean age 93 years; age range 90-106 years) followed for 6 years survival, belonging to 552 sib-ships (familiar longevity) recruited (2005)(2006)(2007)(2008) within the EU-funded GEHA project in three Italian geographic areas (Northern, Central and Southern Italy) different for urban/rural and socio-economical characteristics. On the whole, the following factors emerged as significant predictors of survival after 90 years of age: absence of cognitive impairment and physical disability, high hand grip strength scores and body mass index (BMI) values, "excellent/good" self-reported health, high haemoglobin and total cholesterol levels and low creatinine levels. These parameters, excluding BMI values, were also significantly associated within sib-ships, suggesting a strong familial/genetic component. Geographical micro-heterogeneity of survival predictors emerged, such as functional and physical status being more important in Southern than in Central and Northern Italy. In conclusion, we identified modifiable survival predictors related to specific domains, whose role and importance vary according to the geographic area considered and which can help in interpreting the genetic results obtained by the GEHA project, whose major aim is the comprehensive evaluation of phenotypic and genetic data.

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Section: Discussionmentioning

confidence: 99%

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Cevenini¹,

Cotichini²,

Stazi³

et al. 2013

AGE

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“…With logistic regression, generalized estimating equations were used to account for correlations among family members, using proportional odds models for polytomous outcomes (23)(24)(25). Because neither individuals nor families were selected on the basis of retinopathy, the usual definition of a proband as an affected individual through whom a family is ascertained was not applicable.…”

Section: Analysesmentioning

confidence: 99%

Familial Aggregation of Severity of Diabetic Retinopathy in Mexican Americans From Starr County, Texas

et al. 2005

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OBJECTIVE -Diabetic retinopathy is a major cause of blindness. To determine whether retinopathy itself or only its severity aggregates in families, we examined the occurrence and severity of diabetic retinopathy in Mexican-American siblings with type 2 diabetes.RESEARCH DESIGN AND METHODS -Using stereoscopic fundus photography of seven standard fields, we measured retinopathy in 656 type 2 diabetic patients from 282 Mexican-American families from Starr County, Texas. Retinopathy severity was scored using the Early Treatment of Diabetic Retinopathy Study system and classified as no retinopathy, early nonproliferative diabetic retinopathy (NPDR-E), moderate-to-severe nonproliferative diabetic retinopathy (NPDR-S), or proliferative diabetic retinopathy (PDR).RESULTS -Of 249 siblings of randomly selected probands with retinopathy, 169 (67.9%) had retinopathy, compared with 95 of 125 siblings of unaffected probands (76.0%; P ϭ 0.11). Proband retinopathy class was associated (P ϭ 0.03) with sibling retinopathy class, with significant odds ratios (ORs) for NPDR-E versus no retinopathy ) and PDR versus NPDR-E (2.02 [1.13-3.63]); the contrast of NPDR-S versus NPDR-E approached significance (1.78 [0.99 -3.20]). With the more severe classes (PDR and NPDR-S) combined in one group and the less severe ones (none and NPDR-E) in another, more severe proband retinopathy was associated with more severe sibling retinopathy (1.72 [1.03-2.88]).CONCLUSIONS -More severe diabetic retinopathy showed evidence of familial aggregation, but the occurrence of diabetic retinopathy per se did not. The factors involved in the onset of diabetic retinopathy may differ from those involved in its progression to more severe forms. Diabetes Care 28:1163-1168, 2005D iabetic retinopathy, a frequent complication of both type 1 and type 2 diabetes, is the fifth most common cause of blindness in the U.S. (1). Some retinopathy occurs in virtually all type 1 and 60% of type 2 diabetic patients affected Ն20 years, although severe proliferative retinopathy is more frequent in type 1 diabetes. The underlying causes of diabetic retinopathy have not yet been elucidated, although tight control of hyperglycemia can retard its development and progression (1-4).Numerous studies have examined specific genes or chromosomal regions in relation to the risk for diabetic retinopathy. Evidence of linkage between regions on chromosomes 3 and 9 and occurrence of retinopathy has been reported in Pima Indians with type 2 diabetes (5). Polymorphisms in a number of genes have been associated with diabetic retinopathy, although few associations have been replicated (6). Exceptions are aldose reductase (7-14) and the insertion/deletion polymorphism of the ACE gene (15,16), although meta-analysis did not support the latter association (17).Despite studies relating genetic variation to risk of retinopathy, the extent to which diabetic retinopathy aggregates in families has not been clearly established. Concordance for retinopathy was found in 35 of 37 identical twins concordant for ...

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“…25 Generalized estimating equations provide unbiased estimates of sibling recurrence ORs while allowing for the inclusion of covariates and accommodating varying family sizes by using an exchangeable correlation coefficient in the correlation matrix. The statistical analyses were performed in R 26,27 using the geepack library, 28 which was extended to accommodate logistic models and provide sibling recurrence ORs.…”

Section: Methodsmentioning

confidence: 99%

Familial aggregation of hyperopia in an elderly population of siblings in Salisbury, Maryland

Wojciechowski¹,

Congdon²,

Bowie³

et al. 2005

Ophthalmology

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Purpose-To determine whether hyperopia aggregates in families in an older mixed-race population.Design-Cross-sectional familial aggregation study using sibships.Methods-We recruited 759 subjects (mean age, 73.4 years) in 241 families through the population-based Salisbury Eye Evaluation study. Subjects underwent noncycloplegic refraction if best-corrected visual acuity (BCVA) was ≤20/40, had lensometry to measure their currently worn spectacles if BCVA was >20/40 with spectacles, or were considered to be plano (refraction of zero) if the BCVA was >20/40 without spectacles. Preoperative refraction from medical records was used for bilaterally pseudophakic subjects.Results-Utilizing hyperopia cutoffs from 1.00 to 2.50 diopters, age-, race-, and gender-adjusted odds ratios for hyperopia with an affected sibling ranged from 2.72 (95% confidence interval [CI], 1.84-4.01) to 4.87 (95% CI, 2.54-9.30). The odds of hyperopia increased with age until 75 years, after which they remained relatively constant. Black men were significantly less likely to be hyperopic than white men, white women, or black women.Conclusions-Hyperopia appears to be under strong genetic control in this older population.Hyeropia, or farsightedness, describes the refractive state where the focal point of light entering the eye is behind the retina, due to a short axial length relative to the eye's optical system. Hyperopia of >3.0 diopters (D) is estimated to affect 11.8 million persons over the age of 40 years in the United States, or 9.9% of the U.S. population. 1 Though the process of accommodation allows a number of these individuals to see normally without refractive correction, many others require spectacle, contact lens, or surgical correction, with the attendant risk of bacterial keratitis 2 or infection due to surgical correction of refractive error. [3][4][5] Additionally, children with high levels of hyperopia are at risk for accommodative esotropia, a condition that, if untreated, may result in amblyopia, impaired stereoscopic vision, and a significant reduction in vision-related functional status. 6 Although the number of children with accommodative esotropia is not well known, strabismus has been estimated to affect between 0.5% and 4% of children. [7][8][9][10] Esodeviations comprise >50% of this, 11 with refractive accommodative esotropia clearly playing a significant role. Evidence exists suggesting that hyperopia may be under strong genetic control. 14,15 Twin studies in England have suggested that hyperopia, treated as a binary trait, has a heritability of 89%, virtually the same as myopia. 14 Biometric traits such as axial length and radius of corneal curvature, which determine hyperopia, also demonstrated heritability in the 80% to 90% range in the British twin study. However, genetic studies of hyperopia have been far fewer than for myopia. A small number of genetic conditions have been identified that are characterized by hyperopia in conjunction with ocular 16 or systemic 17 abnormalities. To the best of our knowledge...

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Measuring familial aggregation by using odds‐ratio regression models

Cited by 60 publications

References 20 publications

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Familial Aggregation of Severity of Diabetic Retinopathy in Mexican Americans From Starr County, Texas

Familial aggregation of hyperopia in an elderly population of siblings in Salisbury, Maryland

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