Professor Dr. med. Christian Scharfetter

Genetic Diversity in Families with Alcoholism

In the case of genetically complex disorders, like alcohol dependence, the standard phenotype-to-genotype research strategy may not readily lead to the detection of "signals" if the contributions of single loci are small, and if there exist significant interactions between loci. In contrast, the genotype-to-phenotype strategy has its main focus on oligogenic, interacting models that evaluate the within-family similarities of high-dimensional genetic feature vectors. In this approach, the power of detecting "signals" increases with the genetic variation that arises from the existence of various alleles at the different loci, and that is expected to be greatest when there are many alleles at a locus, all at equal frequency.

COGA Study: Affected versus Unaffected Sibs

Using genotypes of 280 marker loci on the 22 autosomes of 105 alcohol-dependent probands, their affected and unaffected sibs, as well as their parents, we iteratively constructed a genetic similarity function that enabled us to quantify the inter-individual genetic distances d(Xi,Xj) between feature vectors Xi, Xj made up by the allelic patterns of individuals i, j with respect to n loci L1, L2, .. Ln. Based on this similarity function, we investigated the sib-sib similarities which are expected to deviate from "0.5" in affected sib pairs if the region of interest contains markers close to disease-causing genes. The reference value "0.5" was derived by evaluating the parent-offspring similarities which are always "0.5", irrespective of the status of affectedness of parents and offspring. Additionally, we determined the eigenvectors that optimally represented the genetic variation ("diversity") associated with the feature vectors.

Genetic Diversity

It turned out that (1) typically 3-4 eigenvectors explained two thirds of the genetic variation inherent to the 8-20 polymorphic markers of each autosome, and (2) several marker configurations on chromosomes 1, 3, 7, 15 and 17 reproducibly discriminated (p <0.01) probands and unaffected sibs on the one hand, and affected and unaffected sibs on the other ("affected vs unaffected"), while no such differences were found between probands and affected sibs ("affected vs affected").

References

Stassen HH, Begleiter H, Porjesz B, Rice J, Scharfetter C, Reich T: Structural decomposition of genetic diversity in families with alcohol dependence. Genetic Analysis Workshop 11: Analysis of genetic and environmental factors in common diseases. Genetic Epidemiology 1999; 17: 325-330

Stassen HH and Scharfetter C: Integration of genetic maps by polynomial transformations. Am J Med Genetics B 2000; 96: 108-113

Stassen HH, Bridler R, Hägele S, Hergersberg M, Mehmann B, Schinzel A, Weisbrod M, Scharfetter C: Schizophrenia and smoking: evidence for a common neurobiological basis? Am J Med Genetics B 2000; 96: 173-177

Hoffmann K, Stassen HH, Reis A: Genkartierung in Isolatpopulationen. Medizinische Genetik 2000; 12,4: 428-437

Stassen HH, Scharfetter C: Oligogenic approaches to the predisposition of asthma in ethnically diverse populations. Genetic Analysis Workshop 12: Analysis of genetic and environmental factors in common diseases. Genetic Epidemiology 2001; 21(1): 284-289

Stassen HH, Hoffmann K, Scharfetter C: Similarity by state/descent and genetic vector spaces: Analysis of a longitudinal family study. Genetic Analysis Workshop 13: Analysis of longitudinal family data for complex diseases and related risk factors. BMC Genet 2003; 4, S59: 1-6

Stassen HH, Bridler R, Hell D, Weisbrod M, Scharfetter C: Ethnicity-independent genetic basis of functional psychoses. A Genotype-to-phenotype approach. Am J Med Genetics B 2004; 124: 101-112

Berger M, Stassen HH, Köhler K, Krane V, Mönks D, Wanner C, Hoffmann K, Hoffmann MM, Zimmer M, Bickeböller H, Lindner TH: Hidden population substructures in an apparently homogeneous population bias association studies. Eur J Hum Genetics 2006; 14: 236-244

Stassen HH, Szegedi A, Scharfetter C: Modeling Activation of Inflammatory Response System. A Molecular-Genetic Neural Network Analysis. BMC Proceedings 2007, 1 (Suppl 1): S61, 1-6

Stassen HH, Hoffmann K, Scharfetter C: The Difficulties of Reproducing Conventionally Derived Results through 500k-Chip Technology. BMC Genet Proc. 2009; 3 Suppl 7: S66

Professor Dr. med. Christian Scharfetter

Dept. of Psychiatry, Psychotherapy & Psychosomatics

Psychiatric Hospital, University of Zurich

Genetic Diversity in Families with Alcoholism

COGA Study: Affected versus Unaffected Sibs

Genetic Diversity

References

Very similar NPL score characteristics for multiplex nuclear families ascertained in 2 independent waves ("Wave-I", "Wave-II") through index-cases with a diagnosis of alcohol dependence indicate reproducibility of vulnerability and protection loci.