Alcohol use disorders (AUDs) are complex traits, meaning that variations in many genes contribute to the risk, as does the environment. Although the total genetic contribution to risk is substantial, ...most individual variations make only very small contributions. By far the strongest contributors are functional variations in 2 genes involved in alcohol (ethanol EtOH) metabolism. A functional variant in alcohol dehydrogenase 1B (ADH1B) is protective in people of European and Asian descent, and a different functional variant in the same gene is protective in those of African descent. A strongly protective variant in aldehyde dehydrogenase 2 (ALDH2) is essentially only found in Asians. This highlights the need to study a wide range of populations. The likely mechanism of protection against heavy drinking and AUDs in both cases is alteration in the rate of metabolism of EtOH that at least transiently elevates acetaldehyde. Other ADH and ALDH variants, including functional variations in ADH1C, have also been implicated in affecting drinking behavior and risk for alcoholism. The pattern of linkage disequilibrium in the ADH region and the differences among populations complicate analyses, particularly of regulatory variants. This critical review focuses upon the ADH and ALDH genes as they affect AUDs.
The genes that have the largest impact on alcohol consumption and Alcohol Use Disorders are alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2); both work by altering the rate of ethanol metabolism to at least transiently elevate acetaldehyde. Different functional variations are important in different populations. ADH1B and ADH4 have also been implicated, but linkage disequilibrium complicates analyses, and other variants may only be proxies for the functional variants.
Alcohol use disorder (AUD) is known to run in families, and related disorders such as drug use and psychiatric disorders are also common in these families. Understanding the factors that contribute ...to this familial aggregation is important for developing effective prevention and treatment strategies. A recent study by Kendler et al. examined parent and offspring data from a large Swedish population sample to determine the transmission of risk for five disorders (AUD, drug use disorders, ADHD, major depression, and anxiety disorders) from parents with AUD to their offspring. The study found that the risk of offspring developing AUD was highest, followed by drug use disorders and ADHD. The risk was similar for sons and daughters, suggesting that the difference in AUD prevalence between men and women is primarily due to environmental factors. The study also found that the risk for offspring of affected mothers and fathers was essentially identical. These findings highlight the importance of both genetic and environmental factors in the development of AUD and related disorders. Further research is needed to understand the underlying mechanisms and develop personalized treatments.
For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on ...clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.
Objective:Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated with ...a proxy measure of alcohol consumption and alcohol misuse and to explore the shared genetic basis between these measures and other substance use, psychiatric, and behavioral traits.Method:This study used quantitative measures from the Alcohol Use Disorders Identification Test (AUDIT) from two population-based cohorts of European ancestry (UK Biobank N=121,604 and 23andMe N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. Two additional GWAS analyses were performed, a GWAS for AUDIT scores on items 1–3, which focus on consumption (AUDIT-C), and for scores on items 4–10, which focus on the problematic consequences of drinking (AUDIT-P).Results:The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; this study also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76–0.92) and DSM-IV alcohol dependence (rg=0.33–0.63). AUDIT-P and AUDIT-C scores showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P score was significantly positively genetically correlated with schizophrenia (rg=0.22), major depressive disorder (rg=0.26), and attention deficit hyperactivity disorder (rg=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (rg=−0.24) and ADHD (rg=−0.10). This study also used the AUDIT data in the UK Biobank to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total scores ≤4 as control subjects and those with scores ≥12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (rg=0.82) while retaining most subjects.Conclusions:AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and alcohol use disorders.
Affymetrix GeneChips are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce ...false positives, but they have rarely been compared or quantitatively evaluated. Here we describe and evaluate a simple method that uses the detection (Present/Absent) call generated by the Affymetrix microarray suite version 5 software (MAS5) to remove data that is not reliably detected before further analysis, and compare this with filtering by expression level. We explore the effects of various thresholds for removing data in experiments of different size (from 3 to 10 arrays per treatment), as well as their relative power to detect significant differences in expression.
Our approach sets a threshold for the fraction of arrays called Present in at least one treatment group. This method removes a large percentage of probe sets called Absent before carrying out the comparisons, while retaining most of the probe sets called Present. It preferentially retains the more significant probe sets (p < or = 0.001) and those probe sets that are turned on or off, and improves the false discovery rate. Permutations to estimate false positives indicate that probe sets removed by the filter contribute a disproportionate number of false positives. Filtering by fraction Present is effective when applied to data generated either by the MAS5 algorithm or by other probe-level algorithms, for example RMA (robust multichip average). Experiment size greatly affects the ability to reproducibly detect significant differences, and also impacts the effect of filtering; smaller experiments (3-5 samples per treatment group) benefit from more restrictive filtering (> or =50% Present).
Use of a threshold fraction of Present detection calls (derived by MAS5) provided a simple method that effectively eliminated from analysis probe sets that are unlikely to be reliable while preserving the most significant probe sets and those turned on or off; it thereby increased the ratio of true positives to false positives.
Genetics and alcoholism Edenberg, Howard J; Foroud, Tatiana
Nature reviews. Gastroenterology & hepatology,
08/2013, Letnik:
10, Številka:
8
Journal Article
Recenzirano
Odprti dostop
Alcohol is widely consumed; however, excessive use creates serious physical, psychological and social problems and contributes to the pathogenesis of many diseases. Alcohol use disorders (that is, ...alcohol dependence and alcohol abuse) are maladaptive patterns of excessive drinking that lead to serious problems. Abundant evidence indicates that alcohol dependence (alcoholism) is a complex genetic disease, with variations in a large number of genes affecting a person's risk of alcoholism. Some of these genes have been identified, including two genes involved in the metabolism of alcohol (ADH1B and ALDH2) that have the strongest known affects on the risk of alcoholism. Studies continue to reveal other genes in which variants affect the risk of alcoholism or related traits, including GABRA2, CHRM2, KCNJ6 and AUTS2. As more variants are analysed and studies are combined for meta-analysis to achieve increased sample sizes, an improved picture of the many genes and pathways that affect the risk of alcoholism will be possible.
Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among ...study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.
With increasing representation of global populations in genetic studies, there is an opportunity for advanced methods development and a need for consensus “best practices” for analyzing datasets. We provide background on the scientific and ethical importance of including underrepresented groups in genetics research and offer guidance for genome-wide analysis of ancestrally diverse study cohorts.
Psychiatric Genomics: An Update and an Agenda Sullivan, Patrick F; Agrawal, Arpana; Bulik, Cynthia M ...
American Journal of Psychiatry,
01/2018, Letnik:
175, Številka:
1
Journal Article
Recenzirano
Odprti dostop
The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. This global effort is dedicated to rapid progress and open science, and in the past decade it has ...delivered an increasing flow of new knowledge about the fundamental basis of common psychiatric disorders. The PGC has recently commenced a program of research designed to deliver “actionable” findings—genomic results that 1) reveal fundamental biology, 2) inform clinical practice, and 3) deliver new therapeutic targets. The central idea of the PGC is to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering a phase of accelerated genetic discovery for multiple psychiatric disorders. These findings are likely to elucidate the genetic portions of these truly complex traits, and this knowledge can then be mined for its relevance for improved therapeutics and its impact on psychiatric practice within a precision medicine framework.AJP at 175: Remembering Our Past As We Envision Our FutureNovember 1946: The Genetic Theory of SchizophreniaFranz Kallmann’s influential twin study of schizophrenia in 691 twin pairs was the largest in the field for nearly four decades. (Am J Psychiatry 1946; 103:309–322)
Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is ...not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.
PDF
