Die Dermatitis digitalis (DD) ist eine weltweit verbreitete infektiöse Klauenerkrankung mit negativem Einfluss auf das Wohlbefinden und die Leistung von Milchrindern. Durch die multifaktoriell bedingte Ätiologie und die unterschiedlichen klinischen Erscheinungsformen gestaltet sich die Therapie und Prophylaxe der Erkrankung als schwierig. Schätzungen für Erblichkeiten im moderaten Bereich und die Identifizierung von verschiedenen Kuhtypen hinsichtlich der Anfälligkeit für DD unterstreichen die mögliche Beteiligung von wirtseigenen genetischen Faktoren an der Entstehung der Erkrankung. Unter Anwendung einer intensiven Phänotypisierung DD-betroffener Tiere wurden im Rahmen dieser Arbeit genetisch bedingte Hintergründe der Erkrankung untersucht, Erblichkeiten berechnet und eine Zuchtwertschätzung für DD entwickelt. Zudem war beabsichtigt über eine genomweite Assoziationsstudie (GWAS) relevante chromosomale Bereiche, Kandidatengene und funktionelle Gengruppen für Merkmale, die die Anfälligkeit und den Verlauf der Erkrankung beschreiben, zu identifizieren. Die Ergebnisse der vorliegenden Arbeit liefern neue Erkenntnisse hinsichtlich einer züchterischen sowie genomischen Bearbeitung der DD des Holstein-Rindes. Dabei stellt die Nutzung von Phänotypen aus der wiederholten Einstufung von Kühen mittels M-Stadien-Klassifizierungssystem eine Innovation gegenüber der bisherigen Zuchtwertschätzung für Klauenerkrankungen dar. Insgesamt bestätigen die Ergebnisse eine bereits angenommene polygenetische Beeinflussung der DD beim Holstein-Rind. Eine gezielte züchterische Bearbeitung sollte flächendeckend und ergänzend zu allgemeinen Präventions- und therapeutischen Maßnahmen eingesetzt werden.

No description available.

Die Linksventrikuläre Noncompaction des Myokards (LVNC) ist eine seltene primäre Herzmuskelerkrankung. Es wird angenommen, dass es sich um eine embryonale Entwicklungsstörung des Myokards handelt. Mutationen in dem X-chromosomalen Gen TAZ sind verantwortlich für Fälle von frühkindlicher LVNC während die genetische Ursache autosomal-dominant vererbter adulter LVNC weitgehend unbekannt ist. In dieser Arbeit wurde die genetische Ursache der LVNC in der Familie LVNC-105 untersucht. Weiterhin wurden in einem großen Kollektiv von LVNC-Indexpatienten Kandidatengenanalysen durchgeführt. Bei der Familie LVNC-105 zeigte die genomweite Kopplungsanalyse nur signifikant hohe 2-Punkt-LOD-Werte auf Chromosom 11p15. Der maximale 2-Punkt-LOD-Wert betrug 5,06 bei D11S902 und der Lokus konnte auf 3,2 Mb (4,9 cM) eingeengt werden. Unter den 40 Genen des Erkrankungslokus war das Kandidatengen CSRP3, das bereits für 2 andere Kardiomyopathien, die dilatative und die hypertrophe Kardiomyopathie (DCM und HCM), als Krankheitsgen beschrieben wurde. Die Sequenzierung des genomischen Bereichs von CSRP3 zeigte keine Mutation bei den betroffenen Familienmitgliedern. Auch die Analyse von weiteren, im Lokus enthaltenen Gene ergab keine Mutation in kodierenden Exons. Auch Untersuchungen auf Transkriptebene offenbarten keine genetische Veränderung. Bei der Sequenzierung der LVNC-Kandidatengene LDB3, LMNA, Nkx2.5 und\linebreak BMP10 bei 63 erwachsenen Indexpatienten mit isolierter LVNC wurde nur eine Mutation in LDB3 gefunden. Erstmals wurden auch 7 Gene, die für sarkomere Proteine kodieren und als Krankheitsgene für HCM und DCM bekannt sind, mittels DHPLC untersucht. Es wurden Mutationen in einem großen Anteil der LVNC-Indexpatienten (19%) in MYH7, ACTC, TPM1 und TNNT2 identifiziert. Klinische Untersuchungen zeigten bei 7 von 12 Patienten mit Mutationen das Vorliegen einer familiären LVNC. In 4 autosomal-dominanten LVNC-Familien kosegregierten die MYH7 Mutationen mit der Erkrankung. MYH7 war mit einem Anteil von 13% das häufigste Krankheitsgen. Die Mutationen in MYH7 lagen vorwiegend in der ATP-Bindungsstelle. LVNC gehört damit zum Spektrum der Kardiomyopathien, die durch Mutationen in sarkomeren Proteinen hervorgerufen werden können. / Left ventricular noncompaction of the myocardium (LVNC) constitutes a rare primary cardiomyopathy. The mechanistic basis is assumed to be an arrest in embryonic cardiac development. Mutations in the X-linked TAZ gene are responsible for cases of infantile LVNC whereas the genetic base of late-onset LVNC in most patients is still unresolved. The objectives of this dissertation were to investigate the genetic defect in family LVNC-105 with autosomal dominant inherited LVNC and to screen a large cohort of patients with isolated LVNC for mutations in candidate genes. In kindred LVNC-105 genome wide linkage analysis revealed significant two-point LOD scores only at chromosome 11p15. A peak 2-point LOD score of 5.06 was obtained with marker D11S902 and a critical interval of 3.2 Mb (4.9 cM) was determined. Among the 40 genes within the disease region one candidate gene was CSRP3, a disease gene for hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Sequence analysis of the genomic CSRP3 region did not reveal mutations in affected family members. Also, analysis of the coding region of further candidate genes contained within the disease locus did not show mutations. Investigations of the genes on transcript level did not detect alterations. Candidate gene analysis of LDB3, LMNA, Nkx2.5 and BMP10 in 63 index patients with isolated LVNC only one mutation was detected in LDB3. For the first time 7 genes encoding sarcomere proteins, known as disease genes for HCM and DCM, were screened for mutations by DHPLC in LVNC patients. Mutations were found in a significant proportion of the cohort of LVNC index patients (19%) in MYH7, ACTC, TPM1 and TNNT2. Clinical evaluations demonstrated familial disease in 7 of 12 probands with sarcomere gene mutations. MYH7 mutations segregated with the disease in 4 autosomal dominant LVNC kindreds. MYH7 was identified as the most prevalent LVNC disease gene (13%) in this cohort. Modified residues in MYH7 were mainly located within the ATP binding site. In conclusion, LVNC belongs to the spectrum of cardiomyopathies originating in molecular defects of the sarcomere.

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75×10−6 and 8.3×10−7. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.

No description available.

No description available.

For more than half a decade, lithium has been successfully used to treat bipolar disorder. Worldwide, it is considered the first-line mood stabilizer. Apart from its proven antimanic and prophylactic effects, considerable evidence also suggests an antisuicidal effect in affective disorders. Lithium is also effectively used to augment antidepressant drugs in the treatment of refractory major depressive episodes and prevent relapses in recurrent unipolar depression. In contrast to many psychiatric drugs, lithium has outlasted various pharmacotherapeutic ‘fashions’, and remains an indispensable element in contemporary psychopharmacology. Nevertheless, data from pharmacogenetic studies of lithium are comparatively sparse, and these studies are generally characterized by small sample sizes and varying definitions of response. Here, we present an international effort to elucidate the genetic underpinnings of lithium response in bipolar disorder. Following an initiative by the International Group for the Study of Lithium-Treated Patients (www.IGSLI.org) and the Unit on the Genetic Basis of Mood and Anxiety Disorders at the National Institute of Mental Health,lithium researchers from around the world have formed the Consortium on Lithium Genetics (www.ConLiGen.org) to establish the largest sample to date for genome-wide studies of lithium response in bipolar disorder, currently comprising more than 1,200 patients characterized for response to lithium treatment. A stringent phenotype definition of response is one of the hallmarks of this collaboration. ConLiGen invites all lithium researchers to join its efforts. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75×10−6 and 8.3×10−7. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.

Die biotechnologischen Entwicklungen der letzten Jahre ermöglichen eine immer detailliertere Untersuchung von genetischen und molekularen Markern mit multiplen komplexen Traits. Allerdings liefern vorhandene statistische Methoden für diese komplexen Analysen oft keine valide Inferenz. Das erste Ziel der vorliegenden Arbeit ist, zwei neue statistische Methoden für Assoziationsstudien von genetischen Markern mit multiplen Phänotypen zu entwickeln, effizient und robust zu implementieren, und im Vergleich zu existierenden statistischen Methoden zu evaluieren. Der erste Ansatz, C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes), ermöglicht die Assoziation von genetischen Varianten mit multiplen Traits in einem gemeinsamen Copula Modell zu untersuchen. Der zweite Ansatz, CIEE (Causal Inference using Estimating Equations), ermöglicht direkte genetische Effekte zu schätzen und testen. C-JAMP wird in dieser Arbeit für Assoziationsstudien von seltenen genetischen Varianten mit quantitativen Traits evaluiert, und CIEE für Assoziationsstudien von häufigen genetischen Varianten mit quantitativen Traits und Ereigniszeiten. Die Ergebnisse von umfangreichen Simulationsstudien zeigen, dass beide Methoden unverzerrte und effiziente Parameterschätzer liefern und die statistische Power von Assoziationstests im Vergleich zu existierenden Methoden erhöhen können - welche ihrerseits oft keine valide Inferenz liefern. Für das zweite Ziel dieser Arbeit, neue genetische und transkriptomische Marker für kardiometabolische Traits zu identifizieren, werden zwei Studien mit genom- und transkriptomweiten Daten mit C-JAMP und CIEE analysiert. In den Analysen werden mehrere neue Kandidatenmarker und -gene für Blutdruck und Adipositas identifiziert. Dies unterstreicht den Wert, neue statistische Methoden zu entwickeln, evaluieren, und implementieren. Für beide entwickelten Methoden sind R Pakete verfügbar, die ihre Anwendung in zukünftigen Studien ermöglichen. / In recent years, the biotechnological advancements have allowed to investigate associations of genetic and molecular markers with multiple complex phenotypes in much greater depth. However, for the analysis of such complex datasets, available statistical methods often don’t yield valid inference. The first aim of this thesis is to develop two novel statistical methods for association analyses of genetic markers with multiple phenotypes, to implement them in a computationally efficient and robust manner so that they can be used for large-scale analyses, and evaluate them in comparison to existing statistical approaches under realistic scenarios. The first approach, called the copula-based joint analysis of multiple phenotypes (C-JAMP) method, allows investigating genetic associations with multiple traits in a joint copula model and is evaluated for genetic association analyses of rare genetic variants with quantitative traits. The second approach, called the causal inference using estimating equations (CIEE) method, allows estimating and testing direct genetic effects in directed acyclic graphs, and is evaluated for association analyses of common genetic variants with quantitative and time-to-event traits. The results of extensive simulation studies show that both approaches yield unbiased and efficient parameter estimators and can improve the power of association tests in comparison to existing approaches, which yield invalid inference in many scenarios. For the second goal of this thesis, to identify novel genetic and transcriptomic markers associated with cardiometabolic traits, C-JAMP and CIEE are applied in two large-scale studies including genome- and transcriptome-wide data. In the analyses, several novel candidate markers and genes are identified, which highlights the merit of developing, evaluating, and implementing novel statistical approaches. R packages are available for both methods and enable their application in future studies.

For more than half a decade, lithium has been successfully used to treat bipolar disorder. Worldwide, it is considered the first-line mood stabilizer. Apart from its proven antimanic and prophylactic effects, considerable evidence also suggests an antisuicidal effect in affective disorders. Lithium is also effectively used to augment antidepressant drugs in the treatment of refractory major depressive episodes and prevent relapses in recurrent unipolar depression. In contrast to many psychiatric drugs, lithium has outlasted various pharmacotherapeutic ‘fashions’, and remains an indispensable element in contemporary psychopharmacology. Nevertheless, data from pharmacogenetic studies of lithium are comparatively sparse, and these studies are generally characterized by small sample sizes and varying definitions of response. Here, we present an international effort to elucidate the genetic underpinnings of lithium response in bipolar disorder. Following an initiative by the International Group for the Study of Lithium-Treated Patients (www.IGSLI.org) and the Unit on the Genetic Basis of Mood and Anxiety Disorders at the National Institute of Mental Health,lithium researchers from around the world have formed the Consortium on Lithium Genetics (www.ConLiGen.org) to establish the largest sample to date for genome-wide studies of lithium response in bipolar disorder, currently comprising more than 1,200 patients characterized for response to lithium treatment. A stringent phenotype definition of response is one of the hallmarks of this collaboration. ConLiGen invites all lithium researchers to join its efforts. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.