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Inbreeding has been shown in almost all species to be associated with impairment of function because of homozygosity of recessive alleles. This occurs across a wide range of traits and suggests a large number of deleterious alleles in the human genome. This has been predicted from the reduced early survival of offspring in first cousin marriages and from similar results in other organisms. (1-3) As most identified genetic variants causing complex disease in humans are partially recessive (1) we predict that inbreeding in humans might influence a wide range of complex diseases.
Numerous reports on the health effects of inbreeding have focused mainly on its impact on reproduction, childhood mortality, and rare Mendelian disorders. (2) (3) For example, a 4-5% increase in childhood mortality has been found in the offspring of first cousin marriages, and similar results have been reported in other species. (2) (4) (5) However, the effects of inbreeding on late onset disorders are largely unknown, despite the fact that deleterious effects of inbreeding in other species are known to increase with age, as predicted by selection theory. (6) (7) The reported finding of greater inbreeding effects for traits such as blood pressure and serum cholesterol in middle age compared with early adult life is consistent with this. (8)
J Med Genet 2003;40:925-932
In order to investigate the hypothesis that the heritable component of late onset diseases includes a major class of deleterious recessive alleles, (9) we recently studied the effects of inbreeding on blood pressure among 2760 adult individuals from 25 villages in a Dalmatian island isolate. The study showed a large effect of inbreeding on blood pressure equivalent to a rise in systolic blood pressure of ~20 mm Hg and diastolic blood pressure of ~12 mm Hg in offspring of first cousin marriages. The effect appeared to be mediated by several hundred recessive alleles as a result of increased homozygosity. (10) In support of this finding, several studies of small inbred communities worldwide have reported an increased prevalence of hypertension. (8) (11-15)
In the present study, we extend this observation by investigating the relation between inbreeding and the prevalence of 10 late onset complex diseases of public health importance. The study was carried out in 14 of the original 25 isolate villages on three neighbouring islands in middle Dalmatia, Croatia. These island populations present a wide range of levels of inbreeding and endogamy, reduced genetic variation at both individual and (sub)population levels, and relative uniformity of environment, (10) (16-18) and thus provide a good setting for investigating inbreeding effects.
The village populations of three neighbouring islands in the eastern Adriatic, part of Middle Dalmatia, Croatia (Brac, Hvar, and Korcula, see fig 1), represent well characterised genetic isolates. The tendency towards inbreeding in each village has been influenced by geographic isolation, political ("Pastrovic") privileges given to residents of certain communities, and sociocultural factors. (16-18) A survey of 1339 adult individuals selected randomly from voting lists to form approximately 20-30% of the total population of these 14 villages was undertaken in late 1970s and early 1980s by the Institute for Anthropological Research in Zagreb in collaboration with the Smithsonian Institute, Washington, USA. The mean adult ages in individual villages varied from 41 to 65 years (detailed age/sex profiles for each village are given in appendix 1). For each individual, information was collected on the highest level of education, occupation, diet, smoking habits, and body mass index (table 1).
Computation of individual inbreeding coefficients
A single researcher (IR) computed individual inbreeding coefficients for each study participant, based on pedigree information on four to five ancestral generations, recorded during the initial field work and supplemented by a study of parish registries. The individual inbreeding coefficients (F) were then computed according to Wright's path method (19).
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
where [m.sub.i] and [n.sub.i] refer to the number of paths from a common ancestor, and c refers to the number of common ancestors. The genealogical inbreeding coefficient for each village was then computed as the average of all individual F values. To further support these estimates, F was calculated from isonymy as suggested by Tay and Yip, (20) and mean values were derived for each of the 14 villages. Estimates based on isonymy are generally thought to be positively based, and so to provide an upper bound for F (table 1).
Follow up data on disease status of cohort individuals
Population census data in 1981, 1991, and 2001 from study villages show significant depopulation with minimal immigration over the last two decades. Thus only 480 individuals who were still resident in the study villages were available for follow up in the year 2000. Specific diagnostic criteria were established for each of 10 commonly occurring disorders in this population (coronary heart disease, stroke, cancer, schizophrenia, epilepsy, uni/bipolar depression, asthma, adult type diabetes, gout, and peptic ulcer) following those presented in Merck's Manual. In collaboration with local general practitioners, two medical doctors, who were blind to the inbreeding status of each individual, inspected the medical records between March and October 2000 and recorded whenever appropriate diagnostic criteria were met. Diagnoses were supported wherever possible by medical records from the local general hospital in Split.
Statistical analysis and modelling
Disease prevalence was first investigated by comparisons between villages grouped by the level of inbreeding as high, moderate, or low (table 2). Disease prevalence rates were standardised by sex and age to the total population of all 14 villages included in the study, using 10 year age intervals and direct standardisation.
In an attempt to overcome the possible confounding effects of unmeasured environmental exposures or population stratification, the relation between individual inbreeding coefficients and disease outcomes was investigated among the 480 individuals. Data on age, sex, education, occupation, diet, smoking status, village of residence, height, weight, and individual inbreeding coefficient (F) were analysed in a logistic regression with disease status as the outcome. Age and sex were forced into the prediction model irrespective of whether they were formally significant. Other main effects (inbreeding, smoking, height, weight and village) were entered with p = 0.05, and all higher order effects and interactions with p = 0.01.
Population attributable risk
Population attributable risk (PAR) estimates for inbreeding were calculated by logistic regression, allowing for individual differences in the variables village, sex, age, height, weight, and smoking. The appropriate regression was determined as a function of all associated variables (including F), then the probability for each individual of having the disease outcome was calculated assuming an F value set at 0. The sum of all such probabilities, [P.sub.sum], is an estimate of the number affected in the absence of inbreeding, but with other variables remaining unaltered. Then PAR = 1-[P.sub.sum]/[N.sub.aff], where [N.sub.aff] is the actual number of affected individuals. In deriving the PAR …