Phenomics: the systematic study of phenotypes on a genome-wide scale

Genome-wide DNA methylation and gene expression analyses of monozygotic twins discordant for intelligence levels

Human intelligence, as measured by intelligence quotient (IQ) tests, demonstrates one of the highest heritabilities among human quantitative traits. Nevertheless, studies to identify quantitative trait loci responsible for intelligence face challenges because of the small effect sizes of individual genes. Phenotypically discordant monozygotic (MZ) twins provide a feasible way to minimize the effects of irrelevant genetic and environmental factors, and should yield more interpretable results by finding epigenetic or gene expression differences between twins. Here we conducted array-based genome-wide DNA methylation and gene expression analyses using 17 pairs of healthy MZ twins discordant intelligently. ARHGAP18, related to Rho GTPase, was identified in pair-wise methylation status analysis and validated via direct bisulfite sequencing and quantitative RT-PCR. To perform expression profile analysis, gene set enrichment analysis (GSEA) between the groups of twins with higher IQ and their co-twins revealed up-regulated expression of several ribosome-related genes and DNA replication-related genes in the group with higher IQ. To focus more on individual pairs, we conducted pair-wise GSEA and leading edge analysis, which indicated up-regulated expression of several ion channel-related genes in twins with lower IQ. Our findings implied that these groups of genes may be related to IQ and should shed light on the mechanism underlying human intelligence.

The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology.

"You are so beautiful"*: behind women's attractiveness towards the biology of reproduction: a narrative review

Female beauty has always attracted human beings. In particular, beauty has been interpreted in terms of reproductive potential and advantage in selection of mates. We have reviewed the recent literature on female facial and physical beauty with the objective of defining which parameters could influence female attractiveness. Symmetry, averageness, and sexual dimorphism with regards to facial beauty, as well as waist-to-hip ratio (WHR), breast size, and body mass index (BMI) for physical beauty, have been assessed. In current societies, it appears that facial attractiveness results from a mixture of symmetry and averageness of traits, high forehead and cheekbones, small nose and chin, full lips, thin eyebrows, and thick hair. A low WHR reliably characterized physical attractiveness, whereas inconsistencies have been observed in the evaluation of breast size and BMI. The importance of breast size appears to vary with time and sex of evaluators, whereas the impact of BMI is related to socio-economic conditions. The various hypotheses behind beauty and the role of attractiveness in mate choice and sexual selection are here described in terms of continuation of human species. Intriguing associations are emerging between features of attractiveness and some reproductive disorders, as both are substantially influenced by sex steroid hormones.

Making preventive medicine more personalized: implications for exercise-related research

OBJECTIVE

This commentary offers a discussion of the need to consider behavioral interventions such as physical exercise as integral components of personalized medicine.

METHODS

We discuss the concept of personalized medicine and review existing evidence of variability in response to exercise training.

RESULTS

We argue that increased understanding is needed regarding sources of variability in exercise responsiveness, and that such understanding should lead to more tailored, often multimodal interventions.

CONCLUSION

Studies of personalized medicine to date have primarily investigated heterogeneity in drug responsiveness; we believe it is time to begin considering preventive strategies such as exercise within a broader scope of personalized care.

Visualization for understanding of neurodynamical systems

Complex neurodynamical systems are quite difficult to analyze and understand. New type of plots are introduced to help in visualization of high-dimensional trajectories and show global picture of the phase space, including relations between basins of attractors. Color recurrence plots (RPs) display distances from each point on the trajectory to all other points in a two-dimensional matrix. Fuzzy Symbolic Dynamics (FSD) plots enhance this information mapping the whole trajectory to two or three dimensions. Each coordinate is defined by the value of a fuzzy localized membership function, optimized to visualize interesting features of the dynamics, showing to which degree a point on the trajectory belongs to some neighborhood. The variance of the trajectory within the attraction basin plotted against the variance of the synaptic noise provides information about sizes and shapes of these basins. Plots that use color to show the distance between each trajectory point and a larger number of selected reference points (for example centers of attractor basins) are also introduced. Activity of 140 neurons in the semantic layer of dyslexia model implemented in the Emergent neural simulator is analyzed in details showing different aspects of neurodynamics that may be understood in this way. Influence of connectivity and various neural properties on network dynamics is illustrated using visualization techniques. A number of interesting conclusions about cognitive neurodynamics of lexical concept activations are drawn. Changing neural accommodation parameters has very strong influence on the dwell time of the trajectories. This may be linked to attention deficits disorders observed in autism in case of strong enslavement, and to ADHD-like behavior in case of weak enslavement.

Visual systems for interactive exploration and mining of large-scale neuroimaging data archives

While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining.

Characterizing variation in the functional connectome: promise and pitfalls

The functional MRI (fMRI) community has zealously embraced resting state or intrinsic functional connectivity approaches to mapping brain organization. Having demonstrated their utility for charting the large-scale functional architecture of the brain, the field is now leveraging task-independent methods for the investigation of phenotypic variation and the identification of biomarkers for clinical conditions. Enthusiasm aside, questions regarding the significance and validity of intrinsic brain phenomena remain. Here, we discuss these challenges and outline current developments that, in moving the field toward discovery science, permit a shift from cartography toward a mechanistic understanding of the neural bases of variation in cognition, emotion and behavior.

A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

Mapping functional brain activation using [14C]-iodoantipyrine in male serotonin transporter knockout mice

Background

Serotonin transporter knockout mice have been a powerful tool in understanding the role played by the serotonin transporter in modulating physiological function and behavior. However, little work has examined brain function in this mouse model. We tested the hypothesis that male knockout mice show exaggerated limbic activation during exposure to an emotional stressor, similar to human subjects with genetically reduced transcription of the serotonin transporter.

Methodology/Principal Findings

Functional brain mapping using [¹⁴C]-iodoantipyrine was performed during recall of a fear conditioned tone. Regional cerebral blood flow was analyzed by statistical parametric mapping from autoradiographs of the three-dimensionally reconstructed brains. During recall, knockout mice compared to wild-type mice showed increased freezing, increased regional cerebral blood flow of the amygdala, insula, and barrel field somatosensory cortex, decreased regional cerebral blood flow of the ventral hippocampus, and conditioning-dependent alterations in regional cerebral blood flow in the medial prefrontal cortex (prelimbic, infralimbic, and cingulate). Anxiety tests relying on sensorimotor exploration showed a small (open field) or paradoxical effect (marble burying) of loss of the serotonin transporter on anxiety behavior, which may reflect known abnormalities in the knockout animal's sensory system. Experiments evaluating whisker function showed that knockout mice displayed impaired whisker sensation in the spontaneous gap crossing task and appetitive gap cross training.

Conclusions

This study is the first to demonstrate altered functional activation in the serotonin transporter knockout mice of critical nodes of the fear conditioning circuit. Alterations in whisker sensation and functional activation of barrel field somatosensory cortex extend earlier reports of barrel field abnormalities, which may confound behavioral measures relying on sensorimotor exploration.

Efficient replication of over 180 genetic associations with self-reported medical data

While the cost and speed of generating genomic data have come down dramatically in recent years, the slow pace of collecting medical data for large cohorts continues to hamper genetic research. Here we evaluate a novel online framework for obtaining large amounts of medical information from a recontactable cohort by assessing our ability to replicate genetic associations using these data. Using web-based questionnaires, we gathered self-reported data on 50 medical phenotypes from a generally unselected cohort of over 20,000 genotyped individuals. Of a list of genetic associations curated by NHGRI, we successfully replicated about 75% of the associations that we expected to (based on the number of cases in our cohort and reported odds ratios, and excluding a set of associations with contradictory published evidence). Altogether we replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and multiple sclerosis. We found significant variation across categories of conditions in the percentage of expected associations that we were able to replicate, which may reflect systematic inflation of the effects in some initial reports, or differences across diseases in the likelihood of misdiagnosis or misreport. We also demonstrated that we could improve replication success by taking advantage of our recontactable cohort, offering more in-depth questions to refine self-reported diagnoses. Our data suggest that online collection of self-reported data from a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.

The genetics of cognitive impairment in schizophrenia: a phenomic perspective

Cognitive impairments are central to schizophrenia and could mark underlying biological dysfunction but efforts to detect genetic associations for schizophrenia or cognitive phenotypes have been disappointing. Phenomics strategies emphasizing simultaneous study of multiple phenotypes across biological scales might help, particularly if the high heritabilities of schizophrenia and cognitive impairments are due to large numbers of genetic variants with small effect. Convergent evidence is reviewed, and a new collaborative knowledgebase - CogGene - is introduced to share data about genetic associations with cognitive phenotypes, and enable users to meta-analyze results interactively. CogGene data demonstrate the need for larger studies with broader representation of cognitive phenotypes. Given that meta-analyses will probably be necessary to detect the small association signals linking the genome and cognitive phenotypes, CogGene or similar applications will be needed to enable collaborative knowledge aggregation and specify true effects.

The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery

The field of phenomics has been investigating network structure among large arrays of phenotypes, and genome-wide association studies (GWAS) have been used to investigate the relationship between genetic variation and single diseases/outcomes. A novel approach has emerged combining both the exploration of phenotypic structure and genotypic variation, known as the phenome-wide association study (PheWAS). The Population Architecture using Genomics and Epidemiology (PAGE) network is a National Human Genome Research Institute (NHGRI)-supported collaboration of four groups accessing eight extensively characterized epidemiologic studies. The primary focus of PAGE is deep characterization of well-replicated GWAS variants and their relationships to various phenotypes and traits in diverse epidemiologic studies that include European Americans, African Americans, Mexican Americans/Hispanics, Asians/Pacific Islanders, and Native Americans. The rich phenotypic resources of PAGE studies provide a unique opportunity for PheWAS as each genotyped variant can be tested for an association with the wide array of phenotypic measurements available within the studies of PAGE, including prevalent and incident status for multiple common clinical conditions and risk factors, as well as clinical parameters and intermediate biomarkers. The results of PheWAS can be used to discover novel relationships between SNPs, phenotypes, and networks of interrelated phenotypes; identify pleiotropy; provide novel mechanistic insights; and foster hypothesis generation. The PAGE network has developed infrastructure to support and perform PheWAS in a high-throughput manner. As implementing the PheWAS approach has presented several challenges, the infrastructure and methodology, as well as insights gained in this project, are presented herein to benefit the larger scientific community.

Advances in multidisciplinary and cross-species approaches to examine the neurobiology of psychiatric disorders

Current approaches to dissect the molecular neurobiology of complex neuropsychiatric disorders such as schizophrenia and major depression have been rightly criticized for failing to provide benefits to patients. Improving the translational potential of our efforts will require the development and refinement of better disease models that consider a wide variety of contributing factors, such as genetic variation, gene-by-environment interactions, endophenotype or intermediate phenotype assessment, cross species analysis, sex differences, and developmental stages. During a targeted expert meeting of the European College of Neuropsychopharmacology (ECNP) in Istanbul, we addressed the opportunities and pitfalls of current translational animal models of psychiatric disorders and agreed on a series of core guidelines and recommendations that we believe will help guiding further research in this area.

Schizophrenia, "Just the Facts" 6. Moving ahead with the schizophrenia concept: from the elephant to the mouse

The current construct of schizophrenia as a unitary disease is far from satisfactory, and is in need of reconceptualization. The first five papers in our "facts" series reviewed what is known about schizophrenia to date, and a limited number of key facts appear to stand out. Schizophrenia is characterized by persistent cognitive deficits, positive and negative symptoms typically beginning in youth, substantive heritability, and brain structural, functional and neurochemical alterations including dopaminergic dysregulation. Several pathophysiological models have been proposed with differing interpretations of the illness, like the fabled six blind Indian men groping different parts of an elephant coming up with different conclusions. However, accumulating knowledge is integrating the several extant models of schizophrenia etiopathogenesis into unifying constructs; we discuss an example, involving a neurodevelopmental imbalance in excitatory/inhibitory neural systems leading to impaired neural plasticity. This imbalance, which may be proximal to clinical manifestations, could result from a variety of genetic, epigenetic and environmental causes, as well as pathophysiological processes such as inflammation and oxidative stress. Such efforts to "connect the dots" (and visualizing the elephant) are still limited by the substantial clinical, pathological, and etiological heterogeneity of schizophrenia and its blurred boundaries with several other psychiatric disorders leading to a "fuzzy cluster" of overlapping syndromes, thereby reducing the content, discriminant and predictive validity of a unitary construct of this illness. The way ahead involves several key directions: a) choosing valid phenotype definitions increasingly derived from translational neuroscience; b) addressing clinical heterogeneity by a cross-diagnostic dimensional and a staging approach to psychopathology; c) addressing pathophysiological heterogeneity by elucidating independent families of "extended" intermediate phenotypes and pathophysiological processes (e.g. altered excitatory/inhibitory, salience or executive circuitries, oxidative stress systems) that traverse structural, functional, neurochemical and molecular domains; d) resolving etiologic heterogeneity by mapping genomic and environmental factors and their interactions to syndromal and specific pathophysiological signatures; e) separating causal factors from consequences and compensatory phenomena; and f) formulating or reformulating hypotheses that can be refuted/tested, perhaps in the mouse or other experimental models. These steps will likely lead to the current entity of schizophrenia being usefully deconstructed and reconfigured into phenotypically overlapping, but etiopathologically unique and empirically testable component entities (similar to mental retardation, epilepsy or cancer syndromes). The mouse may be the way to rescue the trapped elephant!

How pleiotropic genetics of the musculoskeletal system can inform genomics and phenomics of aging

Genetic study can provide insight into the biologic mechanisms underlying inter-individual differences in susceptibility to (or resistance to) organisms' aging. Recent advances in molecular genetics and genetic epidemiology provide the necessary tools to perform a study of the genetic sources of biological aging. However, to be successful, the genetic study of a complex condition requires a heritable phenotype to be developed and validated. Genome-wide association studies offer an unbiased approach to identify new candidate genes for human diseases. It is hypothesized that convergent results from multiple aging-related traits will point out the genes responsible for the general aging of the organism. This perspective focuses on the musculoskeletal aging as an example of an approach to identify a downstream common pathway that summarizes aging processes. Since the musculoskeletal traits are linked to the state of many vital functions, disability, and ultimately survival rates, we postulate that there is significance in studying musculoskeletal aging. Construction of an integrated phenotype of aging can be achieved based on shared genetics among multiple musculoskeletal biomarkers. Valid biomarkers from other systems of the organism should be similarly explored. The new composite aging score needs to be validated by determining whether it predicts all-cause mortality, incidences of major chronic diseases, and disability late in life. Comprehensive databases on biomarkers of musculoskeletal aging in multiple large cohort studies, along with information on various health outcomes, are needed to validate the proposed measure of biological aging.

Self-Rating of the Effects of Alcohol (SRE): Predictive utility and reliability across interview and self-report administrations

The Self-Rating of the Effects of Alcohol (SRE) is a widely used and well-established measure of the level of response to alcohol. Although the SRE has been successfully used in studies of alcoholism etiology, including genetics, studies to date have not compared the self-report and interview formats. The objectives of this study are to: (a) test the predictive utility of the subscales of the SRE in relation to alcohol problems; and (b) test the reliability of the SRE in interview versus self-report formats. A sample of college drinkers (n=446) completed the SRE in a self-report format along with the Alcohol Use Disorders Identification Test (AUDIT). A subset of participants (n=34) returned to the laboratory and completed the SRE in a face-to-face interview format. All subscales of the SRE were robust predictors of alcohol problems accounting for as much as 25% of the variance in AUDIT scores. In addition, scores obtained via self-report and interview-based SRE were highly correlated (r=.70 to .80). Results support the predictive utility of the SRE and provide initial evidence that the self-report and interview formats produce reliable results and may be combined and/or used interchangeably.

COMT moderates the relation of daily maladaptive coping and pain in fibromyalgia

Forty-five women with fibromyalgia (FM) engaged in a 30-day electronic diary assessment, recording daily ratings of pain and 2 forms of maladaptive coping: pain catastrophizing and pain attention. Participants were genotyped for the val(158)met single nucleotide polymorphism (rs4680) in the catechol-O-methyltransferase (COMT) gene. COMT genotype moderated the daily relations of both maladaptive coping processes and pain. FM women with the homozygous met/met genotype evidenced more pain on days when pain catastrophizing was elevated relative to heterozygous and homozygous val(158) carriers. FM women with the homozygous met/met genotype evidenced more pain on days when pain attention was elevated relative to those with the homozygous val/val genotype. Evidence is presented to suggest that these are independent effects. The findings provide multimeasure and multimethod support for genetic moderation of a maladaptive coping and pain process, which has been previously characterized in a sample of postoperative shoulder pain patients. Further, the findings advance our understanding of the role of COMT in FM, suggesting that genetic variation in the val(158)met polymorphism may affect FM pain through pathways of pain-related cognition. This study examined 2 forms of maladaptive coping: pain catastrophizing and pain attention. The findings provide multimeasure and multimethod support for genetic moderation of a maladaptive coping and pain process and suggest that genetic variation in the val(158)met polymorphism may affect fibromyalgia pain through pathways of pain-related cognition.

Neuropsychology 3.0: evidence-based science and practice

Neuropsychology is poised for transformations of its concepts and methods, leveraging advances in neuroimaging, the human genome project, psychometric theory, and information technologies. It is argued that a paradigm shift toward evidence-based science and practice can be enabled by innovations, including (1) formal definition of neuropsychological concepts and tasks in cognitive ontologies; (2) creation of collaborative neuropsychological knowledgebases; and (3) design of Web-based assessment methods that permit free development, large-sample implementation, and dynamic refinement of neuropsychological tests and the constructs these aim to assess. This article considers these opportunities, highlights selected obstacles, and offers suggestions for stepwise progress toward these goals.

Neurocognitive phenotypes and genetic dissection of disorders of brain and behavior

Elucidating the molecular mechanisms underlying quantitative neurocognitive phenotypes will further our understanding of the brain's structural and functional architecture and advance the diagnosis and treatment of the psychiatric disorders that these traits underlie. Although many neurocognitive traits are highly heritable, little progress has been made in identifying genetic variants unequivocally associated with these phenotypes. A major obstacle to such progress is the difficulty in identifying heritable neurocognitive measures that are precisely defined and systematically assessed and represent unambiguous mental constructs, yet are also amenable to the high-throughput phenotyping necessary to obtain adequate power for genetic association studies. In this perspective we compare the current status of genetic investigations of neurocognitive phenotypes to that of other categories of biomedically relevant traits and suggest strategies for genetically dissecting traits that may underlie disorders of brain and behavior.

Neurogenetic effects on cognition in aging brains: a window of opportunity for intervention?

Knowledge of genetic influences on cognitive aging can constrain and guide interventions aimed at limiting age-related cognitive decline in older adults. Progress in understanding the neural basis of cognitive aging also requires a better understanding of the neurogenetics of cognition. This selective review article describes studies aimed at deriving specific neurogenetic information from three parallel and interrelated phenotype-based approaches: psychometric constructs, cognitive neuroscience-based processing measures, and brain imaging morphometric data. Developments in newer genetic analysis tools, including genome wide association, are also described. In particular, we focus on models for establishing genotype-phenotype associations within an explanatory framework linking molecular, brain, and cognitive levels of analysis. Such multiple-phenotype approaches indicate that individual variation in genes central to maintaining synaptic integrity, neurotransmitter function, and synaptic plasticity are important in affecting age-related changes in brain structure and cognition. Investigating phenotypes at multiple levels is recommended as a means to advance understanding of the neural impact of genetic variants relevant to cognitive aging. Further knowledge regarding the mechanisms of interaction between genetic and preventative procedures will in turn help in understanding the ameliorative effect of various experiential and lifestyle factors on age-related cognitive decline.

Using a parent survey to advance knowledge about the nature and consequences of fragile X syndrome

Understanding the nature and consequences of intellectual and developmental disabilities is challenging, especially when the condition is rare, affected individuals are geographically dispersed, and/or resource constraints limit large-scale studies involving direct assessment. Surveys provide an alternative methodology for gathering information but must be carefully designed and interpreted in light of obvious limitations. In this paper we discuss the potential of surveys in understanding a disabling condition; delineate characteristics of successful survey research; describe a survey of families of individuals with fragile X syndrome; and synthesize major findings. The survey has provided new information about the nature and consequences of fragile X syndrome in a cost-effective fashion, suggesting that survey methodology has a useful place in creating new knowledge about intellectual and developmental disabilities.

Genome-wide pleiotropy of osteoporosis-related phenotypes: the Framingham Study

Genome-wide association studies offer an unbiased approach to identify new candidate genes for osteoporosis. We examined the Affymetrix 500K + 50K SNP GeneChip marker sets for associations with multiple osteoporosis-related traits at various skeletal sites, including bone mineral density (BMD, hip and spine), heel ultrasound, and hip geometric indices in the Framingham Osteoporosis Study. We evaluated 433,510 single-nucleotide polymorphisms (SNPs) in 2073 women (mean age 65 years), members of two-generational families. Variance components analysis was performed to estimate phenotypic, genetic, and environmental correlations (rho(P), rho(G), and rho(E)) among bone traits. Linear mixed-effects models were used to test associations between SNPs and multivariable-adjusted trait values. We evaluated the proportion of SNPs associated with pairs of the traits at a nominal significance threshold alpha = 0.01. We found substantial correlation between the proportion of associated SNPs and the rho(P) and rho(G) (r = 0.91 and 0.84, respectively) but much lower with rho(E) (r = 0.38). Thus, for example, hip and spine BMD had 6.8% associated SNPs in common, corresponding to rho(P) = 0.55 and rho(G) = 0.66 between them. Fewer SNPs were associated with both BMD and any of the hip geometric traits (eg, femoral neck and shaft width, section moduli, neck shaft angle, and neck length); rho(G) between BMD and geometric traits ranged from -0.24 to +0.40. In conclusion, we examined relationships between osteoporosis-related traits based on genome-wide associations. Most of the similarity between the quantitative bone phenotypes may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in defining the best phenotypes to be used in genetic studies of osteoporosis.

Benefits of neuropsychiatric phenomics: example of the 5-lipoxygenase-leptin-Alzheimer connection

Phenomics is a systematic study of phenotypes on a genomewide scale that is expected to unravel, as of yet, unsuspected functional roles of the genome. It remains to be determined how to optimally approach and analyze the available phenomics databases to spearhead innovation in neuropsychiatry. By serendipitously connecting two unrelated phenotypes of increased blood levels of the adipokine leptin, a molecule that regulates appetite, in 5-lipoxygenase- (5-LOX) deficient mice and patients with a lower risk for Alzheimer's disease (AD), we postulated a leptin-mediated basis for beneficial effects of ALOX5 (a gene encoding 5-LOX) gene-deficiency in AD. We suggest that it might be possible to avoid relying on serendipity and develop data-mining tools capable of extracting from phenomics databases indications for such novel hypotheses. Hence, we provide an example of using a free-access Arrowsmith two-node search interface to identify ALOX5 as unsuspected putative mechanisms for the previously described clinical association between increased plasma levels of leptin and a lower risk of incident dementia and AD.

Researching genetic versus nongenetic determinants of disease: a comparison and proposed unification

Research standards deviate in genetic versus nongenetic epidemiology. Besides some immutable differences, such as the correlation pattern between variables, these divergent research standards can converge considerably. Current research designs that dissociate genetic and nongenetic measurements are reaching their limits. Studies are needed that massively measure genotypes, nongenetic exposures, and outcomes concurrently.

PhenoHM: human-mouse comparative phenome-genome server

PhenoHM is a human–mouse comparative phenome–genome server that facilitates cross-species identification of genes associated with orthologous phenotypes (http://phenome.cchmc.org; full open access, login not required). Combining and extrapolating the knowledge about the roles of individual gene functions in the determination of phenotype across multiple organisms improves our understanding of gene function in normal and perturbed states and offers the opportunity to complement biologically the rapidly expanding strategies in comparative genomics. The Mammalian Phenotype Ontology (MPO), a structured vocabulary of phenotype terms that leverages observations encompassing the consequences of mouse gene knockout studies, is a principal component of mouse phenotype knowledge source. On the other hand, the Unified Medical Language System (UMLS) is a composite collection of various human-centered biomedical terminologies. In the present study, we mapped terms reciprocally from the MPO to human disease concepts such as clinical findings from the UMLS and clinical phenotypes from the Online Mendelian Inheritance in Man knowledgebase. By cross-mapping mouse–human phenotype terms, extracting implicated genes and extrapolating phenotype-gene associations between species PhenoHM provides a resource that enables rapid identification of genes that trigger similar outcomes in human and mouse and facilitates identification of potentially novel disease causal genes. The PhenoHM server can be accessed freely at http://phenome.cchmc.org.

Personal genomes in progress: from the human genome project to the personal genome project

The cost of a diploid human genome sequence has dropped from about $70M to $2000 since 2007- even as the standards for redundancy have increased from 7x to 40x in order to improve call rates. Coupled with the low return on investment for common single-nucleotide polymorphisms, this has caused a significant rise in interest in correlating genome sequences with comprehensive environmental and trait data (GET). The cost of electronic health records, imaging, and microbial, immunological, and behavioral data are also dropping quickly. Sharing such integrated GET datasets and their interpretations with a diversity of researchers and research subjects highlights the need for informed-consent models capable of addressing novel privacy and other issues, as well as for flexible data-sharing resources that make materials and data available with minimum restrictions on use. This article examines the Personal Genome Project's effort to develop a GET database as a public genomics resource broadly accessible to both researchers and research participants, while pursuing the highest standards in research ethics.

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations

MOTIVATION

Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease-gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European-Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP-disease associations for these SNPs.

RESULTS

Four of seven known SNP-disease associations using the PheWAS algorithm were replicated with P-values between 2.8 x 10(-6) and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP-disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance.

AVAILABILITY

The PheWAS software and code translation table are freely available at http://knowledgemap.mc.vanderbilt.edu/research.

Cognition in mouse models of schizophrenia susceptibility genes

Cognitive deficits are core features of psychiatric disorders and contribute substantially to functional outcome. It is still unclear, however, how cognitive deficits are related to underlying genetic liability and overt clinical symptoms. Fortunately, animal models of susceptibility genes can illuminate how the products of disease-associated genetic variants affect brain function and ultimately alter behavior. Using as a reference findings from the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia program and the SchizophreniaGene database, we review cognitive data from mutant models of rare and common genetic variants associated with schizophrenia.

The human phenotype ontology

A standardized, controlled vocabulary allows phenotypic information to be described in an unambiguous fashion in medical publications and databases. The Human Phenotype Ontology (HPO) is being developed in an effort to provide such a vocabulary. The use of an ontology to capture phenotypic information allows the use of computational algorithms that exploit semantic similarity between related phenotypic abnormalities to define phenotypic similarity metrics, which can be used to perform database searches for clinical diagnostics or as a basis for incorporating the human phenome into large-scale computational analysis of gene expression patterns and other cellular phenomena associated with human disease. The HPO is freely available at http://www.human-phenotype-ontology.org.

Personal genomes in progress: from the human genome project to the personal genome project

The cost of a diploid human genome sequence has dropped from about $70M to $2000 since 2007--even as the standards for redundancy have increased from 7x to 40x in order to improve call rates. Coupled with the low return on investment for common single-nucleotide polylmorphisms, this has caused a significant rise in interest in correlating genome sequences with comprehensive environmental and trait data (GET). The cost of electronic health records, imaging, and microbial, immunological, and behavioral data are also dropping quickly. Sharing such integrated GET datasets and their interpretations with a diversity of researchers and research subjects highlights the need for informed-consent models capable of addressing novel privacy and other issues, as well as for flexible data-sharing resources that make materials and data available with minimum restrictions on use. This article examines the Personal Genome Project's effort to develop a GET database as a public genomics resource broadly accessible to both researchers and research participants, while pursuing the highest standards in research ethics.

Neuroscience in the era of functional genomics and systems biology

Advances in genetics and genomics have fuelled a revolution in discovery-based, or hypothesis-generating, research that provides a powerful complement to the more directly hypothesis-driven molecular, cellular and systems neuroscience. Genetic and functional genomic studies have already yielded important insights into neuronal diversity and function, as well as disease. One of the most exciting and challenging frontiers in neuroscience involves harnessing the power of large-scale genetic, genomic and phenotypic data sets, and the development of tools for data integration and mining. Methods for network analysis and systems biology offer the promise of integrating these multiple levels of data, connecting molecular pathways to nervous system function.

Colloquium papers: Numbering the hairs on our heads: the shared challenge and promise of phenomics

Evolution and medicine share a dependence on the genotype-phenotype map. Although genotypes exist and are inherited in a discrete space convenient for many sorts of analyses, the causation of key phenomena such as natural selection and disease takes place in a continuous phenotype space whose relationship to the genotype space is only dimly grasped. Direct study of genotypes with minimal reference to phenotypes is clearly insufficient to elucidate these phenomena. Phenomics, the comprehensive study of phenotypes, is therefore essential to understanding biology. For all of the advances in knowledge that a genomic approach to biology has brought, awareness is growing that many phenotypes are highly polygenic and susceptible to genetic interactions. Prime examples are common human diseases. Phenomic thinking is starting to take hold and yield results that reveal why it is so critical. The dimensionality of phenotypic data are often extremely high, suggesting that attempts to characterize phenotypes with a few key measurements are unlikely to be completely successful. However, once phenotypic data are obtained, causation can turn out to be unexpectedly simple. Phenotypic data can be informative about the past history of selection and unexpectedly predictive of long-term evolution. Comprehensive efforts to increase the throughput and range of phenotyping are an urgent priority.

From the genome to the phenome and back: linking genes with human brain function and structure using genetically informed neuroimaging

In recent years, an array of brain mapping techniques has been successfully employed to link individual differences in circuit function or structure in the living human brain with individual variations in the human genome. Several proof-of-principle studies provided converging evidence that brain imaging can establish important links between genes and behaviour. The overarching goal is to use genetically informed brain imaging to pinpoint neurobiological mechanisms that contribute to behavioural intermediate phenotypes or disease states. This special issue on "Linking Genes to Brain Function in Health and Disease" provides an overview over how the "imaging genetics" approach is currently applied in the various fields of systems neuroscience to reveal the genetic underpinnings of complex behaviours and brain diseases. While the rapidly emerging field of imaging genetics holds great promise, the integration of genetic and neuroimaging data also poses major methodological and conceptual challenges. Therefore, this special issue also focuses on how these challenges can be met to fully exploit the synergism of genetically informed brain imaging.