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Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression. Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

A long-established hypothesis is that schizophrenia has a strong genetic component. In the early 1990s, the first genetic variant that substantially increases risk for psychosis was identified. Since this initial reporting of deletions in the chromosomal region 22q11.2, nearly two decades passed until substantial insights into schizophrenia’s genetic architecture were gained. Schizophrenia is a polygenic disorder and genetic risk is conferred by both common and rare alleles distributed across the genome. A small number of rare, deleterious copy number variants (CNVs) are associated with moderate to substantial increases in individual risk to schizophrenia. These deletions and duplications are also associated with a range of neurodevelopmental disorders. The diagnostic investigation of CNVs in patients with schizophrenia is likely to represent one of the first examples of genetic testing in clinical psychiatry. The prerequisites for this are currently being defined.

Polygenic factors are relevant for the genetic predispositions to the eating disorder anorexia nervosa (AN). The most recent genome-wide association study (GWAS) for AN comprised almost 17,000 patients with AN and controls. A total of eight genome-wide significant polygenic loci associated with AN have been identified. Each single polygenic locus makes only a small contribution to the development of AN. Analyses across different traits successfully identified regions/genes for AN that had not been detected by analyses of the single traits. Functional studies of the genes derived by GWAS studies aim to improve the understanding of the biological mechanisms involved in eating disorders. Epigenetic studies have not yet successfully contributed to the understanding of AN.

Autism spectrum disorders (ASDs) are phenotypically as well as genetically heterogeneous developmental disorders with a strong heritability. Clinical and basic science research has described many replicated genetic risk factors. Many findings can well be translated into clinical human genetic practice. The current article summarizes results of genetic studies in ASD, provides a diagnostic algorithm for the clinical human genetic work-up reflecting the German health care system options and gives information with regard to the obligatory genetic counselling after a clinical genetic assessment.

Propensity to psychiatric disease involves the contribution of multiple genetic variants with small individual effects ( i. e. , polygenicity). This contribution can be summarized using polygenic scores (PGSs). The present article discusses the methodological foundations of PGS calculation, together with the limitations and caveats of their use. Furthermore, we show that in terms of using genetic information to address the complexities of mental disorders, PGSs have become a standard tool in psychiatric research. PGS also have the potential for translation into clinical practice. Although PGSs alone do not allow reliable disease prediction, they have major potential value in terms of risk stratification, the identification of disorder subtypes, functional investigations, and case selection for experimental models. However, given the stigma associated with mental illness and the limited availability of effective interventions, risk prediction for common psychiatric disorders must be approached with particular caution, particularly in the non-regulated consumer context.

Brain imaging genomics is an emerging discipline in which genomic and brain imaging data are integrated in order to elucidate the molecular mechanisms that underly brain phenotypes and diseases, including neuropsychiatric disorders. As with all genetic analyses of complex traits and diseases, brain imaging genomics has evolved from small, individual candidate gene investigations towards large, collaborative genome-wide association studies. Recent investigations, mostly population-based, have studied well-powered cohorts comprising tens of thousands of individuals and identified multiple robust associations of single-nucleotide polymorphisms and copy number variants with structural and functional brain phenotypes. Such systematic genomic screens of millions of genetic variants have generated initial insights into the genetic architecture of brain phenotypes and demonstrated that their etiology is polygenic in nature, involving multiple common variants with small effect sizes and rare variants with larger effect sizes. Ongoing international collaborative initiatives are now working to obtain a more complete picture of the underlying biology. As in other complex phenotypes, novel approaches – such as gene–gene interaction, gene–environment interaction, and epigenetic analyses – are being implemented in order to investigate their contribution to the observed phenotypic variability. An important consideration for future research will be the translation of brain imaging genomics findings into clinical practice.

Epigenetic modifications play a key role in development and cell type specificity. These modifications seem to be particularly critical for brain development, where mutations in epigenetic enzymes have been associated with neurodevelopmental disorders as well as with the function of post-mitotic neurons. Epigenetic modifications can be influenced by genetic and environmental factors, both known major risk factors for psychiatric disorders. Epigenetic modifications may thus be an important mediator of the effects of genetic and environmental risk factors on cell function. This review summarizes the different types of epigenetic regulation and then focuses on the mechanisms transducing environmental signals, especially adverse life events that are major risk factors for psychiatric disorders, into lasting epigenetic changes. This is followed by examples of how the environment can induce epigenetic changes that relate to the risk of psychiatric disorders.

Zusammenfassung Seit der Einführung des flächendeckenden Neugeborenen-Screenings auf Phenylketonurie Ende der 60er Jahre in Deutschland, ist die Anzahl der Zielerkrankungen im sogenannten erweiterten Neugeborenen-Screening (ENS) stetig gestiegen. Aufgrund neuer diagnostischer Möglichkeiten, sowie neuer therapeutischer Ansätze bei schweren, seltenen Erkrankungen z. B. des Stoffwechsels, wird die Anzahl der Zielkrankheiten absehbar weiter steigen. Diese werden, unter Berücksichtigung der im vorliegenden Beitrag beschriebenen Grundvoraussetzungen, entweder Teil des erweiterten Neugeborenen-Screenings oder als eigenständiges Screening Teil der Sekundärprävention in Deutschland sein. Dieser Beitrag soll einen Überblick über Grundlagen des etablierten Neugeborenen-Screenings liefern sowie Einblicke in die Voraussetzungen für die Einführung neuer Zielerkrankungen in das Neugeborenen-Screening in Deutschland ermöglichen.

Zusammenfassung Am 1. Februar 2020 wurde das Gendiagnostikgesetz (GenDG) 10 Jahre alt. Damit unterliegen jetzt erstmals Ergebnisse genetischer Analysen und Untersuchungen nicht nur der in der Medizin üblichen 10jährigen Aufbewahrungspflicht, sondern nach deren Ablauf auch der Pflicht zur umgehenden Vernichtung. Bereits bei Inkrafttreten des GenDG am 1. Februar 2010 warf die Vernichtungspflicht nach § 12 Fragen auf, die spätestens seit erstmaligem Ablauf der 10jährigen Aufbewahrungspflicht am 1. Februar 2020 dringend einer Klärung bedürfen. Sie betreffen nicht nur die praktische Umsetzung der Vernichtungspflicht, sondern auch deren Sinnhaftigkeit. Auch die Gendiagnostik-Kommission (GEKO) stellt in ihrem dritten Tätigkeitsbericht die Sinnhaftigkeit der Vernichtungspflicht aus verschiedenen Gründen in Frage und fordert, „den § 12 GenDG auf die Vernichtung von Ergebnissen genetischer Untersuchungen und Analysen zu beschränken, deren Mitteilung von den Betroffenen gemäß § 8 GenDG nicht gewünscht wird.“ (3. Tätigkeitsbericht der GEKO, Seite 39.) Solange jedoch § 12 GenDG in seiner jetzigen Fassung gilt, ist dessen Umsetzung für alle Beteiligten verpflichtend. Dabei sollten bestehende Ausnahmeregelungen großzügig in Anspruch genommen werden, um den Aufwand zu begrenzen und trotzdem den Zweck des Gesetzes zu erfüllen.