Candidate and non-candidate genes in behavior genetics

Flint, Jonathan; Munafò, Marcus R.

doi:10.1016/j.conb.2012.07.005

Cited by 87 publications

(82 citation statements)

References 40 publications

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“…Significantly associated SNPs have an expected effect size <0.5% of the phenotypic variance 8 in quantitative traits, even for measures extracted from images. Work so far by imaging consortia such as ENIGMA and CHARGE suggests that the distribution of effect sizes for brain measures is similar to that seen when studying other quantitative traits, although only the simplest brain measures have so far been assessed with GWAS.…”

Section: Gwas Of Imagingmentioning

confidence: 98%

Whole-genome analyses of whole-brain data: working within an expanded search space

et al. 2014

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Large-scale comparisons of patients and healthy controls have unearthed genetic risk factors associated with a range of neurological and psychiatric illnesses. Meanwhile, brain imaging studies are increasing in size and scope, revealing disease and genetic effects on brain structure and function, and implicating neural pathways and causal mechanisms. With the advent of global neuroimaging consortia, imaging studies are now well powered to discover genetic variants that reliably affect the brain. Genetic analyses of brain measures from tens of thousands of people are being extended to test genetic associations with signals at millions of locations in the brain. Connectome-wide, genome-wide scans can jointly screen brain circuits and genomes, presenting new statistical challenges. There is a growing need for the community to establish and enforce standards in this developing field to ensure robust findings. Here we discuss how neuroimagers and geneticists have formed alliances to discover how genetic factors affect the brain. The field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing. We recommend a rigorous approach to neuroimaging genomics that capitalizes on its recent successes and ensures the reliability of future discoveries.

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Section: Gwas Of Imagingmentioning

confidence: 98%

Whole-genome analyses of whole-brain data: working within an expanded search space

et al. 2014

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“…What remains unequivocal is that data are inconclusive; whether positive or null associations better represent reality can only be addressed by further research. Overall, meta-analytic approaches have provided road maps for challenges associated with candidate studies (60,81) and identified loci conferring small effects for psychiatric and structural neuroimaging phenotypes (16,82). However, the utility of meta-analyses incorporating studies using diverse methodology when study related differences cannot be systemically evaluated, is questionable.…”

Section: Single Variant Approachesmentioning

confidence: 99%

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Bogdan¹,

Salmeron

Carey³

et al. 2017

Biological Psychiatry

150

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Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions including the development of consortia and large scale data collection projects as well as the use of novel methods (e.g., polygenic approaches, machine learning), which enhance the quality of imaging genetic studies, but also introduce new challenges. Here, we critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in its translational and integrative potential with other research approaches (e.g., non-human animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology.

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“…With the candidate gene approach, however, there is no way to verify whether published candidate gene studies are systematically biased toward reporting successes. To correct for this latter problem, it has even been suggested that candidate gene associations should be held to the same significance criterion as GWAS (Flint and Munafo, 2013). The solution will likely require a combination of the two search strategies to iteratively approximate the genetic polymorphisms involved in addiction using both intermediate endophenotypes and well-defined behavioral traits.…”

Section: Genetic Basis Of Addictionmentioning

confidence: 99%

Genetic imaging consortium for addiction medicine

Mackey

Kan

Chaarani

et al. 2016

Progress in Brain Research

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Since the sample size of a typical neuroimaging study lacks sufficient statistical power to explore unknown genomic associations with brain phenotypes, several international genetic imaging consortia have been organized in recent years to pool data across sites. The challenges and achievements of these consortia are considered here with the goal of leveraging these resources to study addiction. The authors of this review have joined together to form an Addiction working group within the framework of the ENIGMA project, a meta-analytic approach to multisite genetic imaging data. Collectively, the Addiction working group possesses neuroimaging and genomic data obtained from over 10,000 subjects. The deadline for contributing data to the first round of analyses occurred at the beginning of May 2015. The studies performed on this data should significantly impact our understanding of the genetic and neurobiological basis of addiction.

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Candidate and non-candidate genes in behavior genetics

Cited by 87 publications

References 40 publications

Whole-genome analyses of whole-brain data: working within an expanded search space

Whole-genome analyses of whole-brain data: working within an expanded search space

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Genetic imaging consortium for addiction medicine

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