Neurofibromatosis 1 (NF1), a genetic condition most commonly characterized by the presence of dermal neurofibromas and café au lait macules, has a significant impact on Quality of Life (QoL). There is a wide range of phenotypic variability, so that affected individuals may have either medically devastating or relatively mild manifestations that do not impact their daily lives. In this study, the SF-36 and Skindex questionnaires were used to quantitatively investigate the impact of severity and visibility on QoL in an American population. Participants were recruited primarily through advertisements distributed by The Children's Tumor Foundation (CTF). The majority participated by completing a mailed questionnaire in which they rated themselves using Ablon's visibility and Riccardi's severity scales, and then completed the SF-36 and Skindex questionnaires. Participants with NF1 reported a significant impact in all aspects of skin-disease-specific QoL, but the emotional aspect demonstrated the greatest effect. Participants with more visible signs of NF1 reported significantly greater overall effects on their skin-disease-specific QoL than those whose manifestations were more subtle. All domains of general health QoL were affected as well, especially in participants who reported having severe complications. Interestingly, greater visibility was not found to be associated with a significant decrease in general health QoL. These findings are consistent with those found in a French cohort, and demonstrate the utility of incorporating tools designed for use in both the general population and for patients with skin disease in examining the impact of NF1 on QoL.

Although mathematical relationships can be proven by deductive logic, biological relationships can only be inferred from empirical observations. This is a distinct disadvantage for those of us who strive to identify the genes involved in complex diseases and quantitative traits. If causation cannot be proven, however, what does constitute sufficient evidence for causation? The philosopher Karl Popper said, "Our belief in a hypothesis can have no stronger basis than our repeated unsuccessful critical attempts to refute it." We believe that to establish causation, as scientists, we must make a serious attempt to refute our own hypotheses and to eliminate all known sources of bias before association becomes causation. In addition, we suggest that investigators must provide sufficient data and evidence of their unsuccessful efforts to find any confounding biases. In this editorial, we discuss what "causation" means in the context of complex diseases and quantitative traits, and we suggest guidelines for steps that may be taken to address possible confounders of association before polymorphisms may be called "causative."

BACKGROUND: 16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure. METHODS: Using voxel-and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV. RESULTS: Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion . control . duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion . control; Cohen's d . 1), the superior and middle temporal gyri (deletion , control; Cohen's d , 21), and the caudate and hippocampus (control . duplication; 20.5 . Cohen's d . 21). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results. CONCLUSIONS: The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder. These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria. Autism spectrum disorder (ASD) and related neurodevelopmental disorders are defined behaviorally and characterized by a significant clinical and etiologic heterogeneity. As a consequence, investigating ASD under the assumption of an underlying homogeneous condition has resulted in controversial findings in the field of neuroimaging (1). Increased brain growth early in development (2-4) and alterations of many regional brain volumes (5) have been implicated in ASD, but results have proven difficult to replicate (1,(6)(7)(8).To mitigate some of these issues, cohorts of individuals with shared genetic risk factors have been assembled to minimize the noise introduced by etiologic and biological heterogeneity (9). Such a "genetic-first" study design provides the opportunity to investigate a given neurodevelopmental risk (and associated mechanism) shared by individuals who carry the same genetic etiology irrespective of the psychiatric diagnosis.Copy number variants (CNVs) at the 16p11.2 (breakpoints 4-5, 29.6-30.2 Mb-hg19) (10) are among the most frequent risk factors for neurodevelopmental and psychiatric conditions.

The last several years has witnessed an explosion in genomics, with the advent of genome-wide association studies revealing hundreds of DNA variants significantly associated with most common diseases, including cancer. On the heels of these scientific advances came the direct-to-consumer (DTC) genetic testing industry. Genome-wide scans for disease have been marketed and sold directly to the public, without the involvement of a health care provider. Unlike genetic testing for mutations in known hereditary cancer susceptibility genes such as BRCA1/2, these genomic profiles examine DNA variants, which typically have a minimal risk impact, and account for only a fraction of the heritable component of cancer. Furthermore, risk information provided to consumers does not account for family history or other known risk factors. The clinical validity and utility of personal genome scans for disease risk prediction remain for the most part unestablished, although some argue lack of evidence of harm and the possibility that positive impacts on health behaviors or genetic awareness may result from consumer use. The DTC genetic testing industry has sparked significant controversy not only among the scientific community, but also among professional societies and government agencies.In this review, we present some of the history and methodological considerations of DTC genomic profiling, with a focus on cancer risk prediction. The literature regarding consumer awareness and utilization is explored, including understanding, expectations, and behavioral and psychological responses to DTC genomic risk prediction. Primary care provider and genetic professional knowledge and perceptions of DTC genomic profiling are also addressed. Ethical and scientific controversy surrounding the DTC genetic testing industry is presented, along with policy recommendations, regulatory actions, and the changing landscape of the DTC genetic testing market in response. Although our understanding of the human genome holds much promise in the realm of cancer prevention and treatment, DTC genomic profiling for cancer risk prediction is unlikely in its current form to have any significant impact on the health of the public. Time will tell if the next venture in genomic medicine, whole genome sequencing, will be accompanied by the translational research and emphasis on public/provider education required to ensure its successful application toward reducing the burden of cancer at a population level.

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.