A.L. Beem

Netherlands twin family study of anxious depression (NETSAD)

In a longitudinal study of Dutch adolescent and young adult twins, their parents and their siblings, questionnaire data were collected on depression, anxiety and correlated personality traits, such as neuroticism. Data were collected by mailed surveys in 1991, 1993, 1995 and 1997. A total of 13,717 individuals from 3344 families were included in the study. To localise quantitative trait loci (QTLs) involved in anxiety and depression, the survey data were used to select the most informative families for a genome-wide search. For each individual a genetic factor score was computed, based on a genetic multivariate analysis of anxiety, depression, neuroticism and somatic anxiety. A family was selected if at least two siblings (or DZ twins) had extreme factor scores. Both discordant (high-low) and concordant (high-high and low-low) pairs were included in the selected sample. Once an extreme sibling pair was selected, all family members (parents and additional siblings of the selected pair) who had at least once returned a questionnaire booklet were asked to provide a DNA sample. In total, 2724 individuals from 563 families (1007 parents and 1717 offspring) were approached and 1975 individuals from 479 families (643 patients and 1332 offspring) complied by returning a buccal swab for DNA isolation. All offspring from selected families were asked to participate in a psychiatric interview and in a 24-hour ambulatory assessment of cardiovascular parameters and cortisol. The interview consisted of the WHO-Composite International Diagnostic Interview and was administered to 1253 offspring. In this paper we describe the genetic-epidemiological analyses of the survey data on anxiety, somatic anxiety, neuroticism and depression. We detail how these data were used to select families for the QTL study and discuss strategies that may help elucidate the molecular pathways leading from genes to anxious depression.

Life events, anxious depression and personality: a prospective and genetic study.

BACKGROUND The association between life events and anxious depression might be due to causality or to gene-environment correlation. We examined unidirectional and reciprocal causality and a gene-environment correlation model, in which genes that influence the vulnerability for anxious depression also increase the risk of exposure to life events. The effect of genes that influence environmental exposure might be mediated through personality and we therefore also examined the association between life events and personality (neuroticism and extraversion). METHOD Information on life events, anxious depression, neuroticism and extraversion was collected in 5782 monozygotic (MZ) and dizygotic (DZ) twins who participated in a longitudinal survey study of the Netherlands Twin Register. To examine causality, data were analysed longitudinally. To examine gene-environment correlation, the co-twin control method was used. RESULTS Anxious depression and, to a lesser extent, neuroticism scores increased after exposure to life events. Anxious depression and neuroticism also predicted the experience of life events. Prospectively, extraversion was not associated with life events. Anxious depression, neuroticism and extraversion scores did not differ between the non-exposed subjects of MZ and DZ twin pairs and unrelated subjects discordant for life events. CONCLUSIONS Our findings suggest that reciprocal causation explains the relationship between life events and anxious depression and between life events and neuroticism. Extraversion is not related to life events. No evidence was found for gene-environment correlation, i.e. the genes that influence anxious depression, neuroticism or extraversion do not overlap with the genes that increase the risk of exposure to life events.

Linkage analysis of smoking initiation and quantity in Dutch sibling pairs

The heritability of smoking initiation (SI) and number of cigarettes smoked (NC) was determined in 3657 Dutch twin pairs. For SI a heritability of 36% was found and for NC of 51%. Both SI and NC were also significantly influenced by environmental factors shared by family members. The etiological factors that influence these traits partly overlap. Linkage analyses were performed on data of 536 DZ twins and siblings from 192 families, forming 592 sibling pairs. Results suggested QTLs on chromosome 6 (LOD=3.05) and chromosome 14 (LOD=1.66) for SI and on chromosome 3 (LOD=1.98) for NC. Strikingly, on chromosome 10 a peak was found in the same region for both SI (LOD=1.92) and for NC (LOD=2.29) which may partly explain the overlapping etiological factors for SI and NC.The heritability of smoking initiation (SI) and number of cigarettes smoked (NC) was determined in 3657 Dutch twin pairs. For SI a heritability of 36% was found and for NC of 51%. Both SI and NC were also significantly influenced by environmental factors shared by family members. The etiological factors that influence these traits partly overlap. Linkage analyses were performed on data of 536 DZ twins and siblings from 192 families, forming 592 sibling pairs. Results suggested QTLs on chromosome 6 (LOD=3.05) and chromosome 14 (LOD=1.66) for SI and on chromosome 3 (LOD=1.98) for NC. Strikingly, on chromosome 10 a peak was found in the same region for both SI (LOD=1.92) and for NC (LOD=2.29) which may partly explain the overlapping etiological factors for SI and NC.

Further evidence for a QTL influencing body mass index on chromosome 7p from a genome-wide scan in Dutch families.

Obesity is a rapidly growing threat to public health, driven by the increased occurrence of high caloric diets and sedentary lifestyles. Within this environment, genetic influences may largely determine inter-individual differences in obesity-related traits. To map genes involved in weight regulation, we performed a genome-wide linkage scan for body mass index (BMI), a reliable measure of total body fat, in 192 Dutch families including 315 twins and 210 siblings with data on BMI. Using variance components linkage analysis, regions with LOD-scores greater than 2 were observed on 6p25.1 (LOD-score, 2.13) and 7p21.1 (LOD-score, 2.40). LOD-scores higher than 1 were found on chromosomes 3, 13, 15 and 21. Of note, evidence for the putative quantitative trait locus for BMI on 7p was obtained previously from such diverse populations as Mexican-Americans, Asians and Nigerians, suggesting that the underlying genes may effect weight regulation in diverse environments. An obvious positional candidate in the 7p linkage region is the gene encoding neuropeptide Y (NPY) that controls satiety and food intake.

A whole-genome scan for 24-hour respiration rate: a major locus at 10q26 influences respiration during sleep.

Identification of genes causing variation in daytime and nighttime respiration rates could advance our understanding of the basic molecular processes of human respiratory rhythmogenesis. This could also serve an important clinical purpose, because dysfunction of such processes has been identified as critically important in sleep disorders. We performed a sib-pair-based linkage analysis on ambulatory respiration rate, using the data from 270 sibling pairs who were genotyped at 374 markers on the autosomes, with an average distance of 9.65 cM. Uni- and multivariate variance-components-based multipoint linkage analyses were performed for respiration rate during three daytime periods (morning, afternoon, and evening) and during nighttime sleep. Evidence of linkage was found at chromosomal locations 3q27, 7p22, 10q26, and 22q12. The strongest evidence of linkage was found for respiration rate during sleep, with LOD scores of 2.36 at 3q27, 3.86 at 10q26, and 1.59 at 22q12. In a simultaneous analysis of these three loci, >50% of the variance in sleep respiration rate could be attributed to a quantitative-trait loci near marker D10S1248 at 10q. Genes in this area (GFRA1, ADORA2L, FGR2, EMX2, and HMX2) can be considered promising positional candidates for genetic association studies of respiratory control during sleep.

Implementation of a combined association-linkage model for quantitative traits in linear mixed model procedures of statistical packages

A transmission disequilibrium test for quantitative traits which combines association and linkage analyses is currently available in several dedicated software packages. We describe how to implement such models in linear mixed model procedures that are available in widely used statistical packages such as SPSS. We also briefly mention a few extensions of the model that become naturally available once the model is implemented in such procedures.