Austen McGuire

Clinically relevant known and candidate genes for obesity and their overlap with human infertility and reproduction

PurposeObesity is a growing public health concern now reaching epidemic status worldwide for children and adults due to multiple problems impacting on energy intake and expenditure with influences on human reproduction and infertility. A positive family history and genetic factors are known to play a role in obesity by influencing eating behavior, weight and level of physical activity and also contributing to human reproduction and infertility. Recent advances in genetic technology have led to discoveries of new susceptibility genes for obesity and causation of infertility. The goal of our study was to provide an update of clinically relevant candidate and known genes for obesity and infertility using high resolution chromosome ideograms with gene symbols and tabular form.MethodsWe used computer-based internet websites including PubMed to search for combinations of key words such as obesity, body mass index, infertility, reproduction, azoospermia, endometriosis, diminished ovarian reserve, estrogen along with genetics, gene mutations or variants to identify evidence for development of a master list of recognized obesity genes in humans and those involved with infertility and reproduction. Gene symbols for known and candidate genes for obesity were plotted on high resolution chromosome ideograms at the 850 band level. Both infertility and obesity genes were listed separately in alphabetical order in tabular form and those highlighted when involved with both conditions.ResultsBy searching the medical literature and computer generated websites for key words, we found documented evidence for 370 genes playing a role in obesity and 153 genes for human reproduction or infertility. The obesity genes primarily affected common pathways in lipid metabolism, deposition or transport, eating behavior and food selection, physical activity or energy expenditure. Twenty-one of the obesity genes were also associated with human infertility and reproduction. Gene symbols were plotted on high resolution ideograms and their name, precise chromosome band location and description were summarized in tabular form.ConclusionsMeaningful correlations in the obesity phenotype and associated human infertility and reproduction are represented with the location of genes on chromosome ideograms along with description of the gene and position in tabular form. These high resolution chromosome ideograms and tables will be useful in genetic awareness and counseling, diagnosis and treatment to improve clinical outcomes.

Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation

A large body of genetic data from schizophrenia‐related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer‐reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high‐resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA‐DRB1, HLA‐DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene‐based treatment as well as provide risk estimates for genetic counseling of families with affected relatives.

Clinically relevant genetic biomarkers from the brain in alcoholism with representation on high resolution chromosome ideograms

OBJECTIVE Alcoholism arises from combined effects of multiple biological factors including genetic and non-genetic causes with gene/environmental interaction. Intensive research and advanced genetic technology has generated a long list of genes and biomarkers involved in alcoholism neuropathology. These markers reflect complex overlapping and competing effects of possibly hundreds of genes which impact brain structure, function, biochemical alcohol processing, sensitivity and risk for dependence. METHOD We compiled a tabular list of clinically relevant genetic biomarkers for alcoholism targeting expression disturbances in the human brain through an extensive search of keywords related to alcoholism, alcohol abuse, and genetics from peer reviewed medical research articles and related nationally sponsored websites. Gene symbols were then placed on high resolution human chromosome ideograms with gene descriptions in tabular form. RESULTS We identified 337 clinically relevant genetic biomarkers and candidate genes for alcoholism and alcohol-responsiveness from human brain research. Genetic biomarkers included neurotransmitter pathways associated with brain reward processes for dopaminergic (e.g., DRD2, MAOA, and COMT), serotoninergic (e.g., HTR3A, HTR1B, HTR3B, and SLC6A4), GABAergic (e.g., GABRA1, GABRA2, and GABRG1), glutaminergic (GAD1, GRIK3, and GRIN2C) and opioid (e.g., OPRM1, OPRD1, and OPRK1) pathways which presumably impact reinforcing properties of alcohol. Gene level disturbances in cellular and molecular networks impacted by alcohol and alcoholism pathology include transketolase (TKT), transferrin (TF), and myelin (e.g., MBP, MOBP, and MOG). CONCLUSIONS High resolution chromosome ideograms provide investigators, physicians, geneticists and counselors a convenient visual image of the distribution of alcoholism genetic biomarkers from brain research with alphabetical listing of genes in tabular form allowing comparison between alcoholism-related phenotypes, and clinically-relevant alcoholism gene(s) at the chromosome band level to guide research, diagnosis, and treatment. Chromosome ideograms may facilitate gene-based personalized counseling of alcohol dependent individuals and their families.

High-resolution chromosome ideogram representation of recognized genes for bipolar disorder.

Bipolar disorder (BPD) is genetically heterogeneous with a growing list of BPD associated genes reported in recent years resulting from increased genetic testing using advanced genetic technology, expanded genomic databases, and better awareness of the disorder. We compiled a master list of recognized susceptibility and genes associated with BPD identified from peer-reviewed medical literature sources using PubMed and by searching online databases, such as OMIM. Searched keywords were related to bipolar disorder and genetics. Our compiled list consisted of 290 genes with gene names arranged in alphabetical order in tabular form with source documents and their chromosome location and gene symbols plotted on high-resolution human chromosome ideograms. The identified genes impacted a broad range of biological pathways and processes including cellular signaling pathways particularly cAMP and calcium (e.g., CACNA1C, CAMK2A, CAMK2D, ADCY1, ADCY2); glutamatergic (e.g., GRIK1, GRM3, GRM7), dopaminergic (e.g., DRD2, DRD4, COMT, MAOA) and serotonergic (e.g., HTR1A, HTR2A, HTR3B) neurotransmission; molecular transporters (e.g., SLC39A3, SLC6A3, SLC8A1); and neuronal growth (e.g., BDNF, IGFBP1, NRG1, NRG3). The increasing prevalence of BPD calls for better understanding of the genetic etiology of this disorder and associations between the observed BPD phenotype and genes. Visual representation of genes for bipolar disorder becomes a tool enabling clinical and laboratory geneticists, genetic counselors, and other health care providers and researchers easy access to the location and distribution of currently recognized BPD associated genes. Our study may also help inform diagnosis and advance treatment developments for those affected with this disorder and improve genetic counseling for families.

Currently recognized clinically relevant and known genes for human reproduction and related infertility with representation on high-resolution chromosome ideograms.

OBJECTIVE To provide an update of currently recognized clinically relevant candidate and known genes for human reproduction and related infertility plotted on high resolution chromosome ideograms (850 band level) and represented alphabetically in tabular form. METHOD Descriptive authoritative computer-based website and peer-reviewed medical literature searches used pertinent keywords representing human reproduction and related infertility along with genetics and gene mutations. A master list of genes associated with human reproduction and related infertility was generated with a visual representation of gene locations on high resolution chromosome ideograms. GeneAnalytics pathway analysis was carried out on the resulting list of genes to assess underlying genetic architecture for infertility. RESULTS Advances in genetic technology have led to the discovery of genes responsible for reproduction and related infertility. Genes identified (N=371) in our search primarily impact ovarian steroidogenesis through sex hormone biology, germ cell production, genito-urinary or gonadal development and function, and related peptide production, receptors and regulatory factors. CONCLUSIONS The location of gene symbols plotted on high resolution chromosome ideograms forms a conceptualized image of the distribution of human reproduction genes. The updated master list can be used to promote better awareness of genetics of reproduction and related infertility and advance discoveries on genetic causes and disease mechanisms.

Morphometric Analysis of Recognized Genes for Autism Spectrum Disorders and Obesity in Relationship to the Distribution of Protein-Coding Genes on Human Chromosomes

Mammalian chromosomes are comprised of complex chromatin architecture with the specific assembly and configuration of each chromosome influencing gene expression and function in yet undefined ways by varying degrees of heterochromatinization that result in Giemsa (G) negative euchromatic (light) bands and G-positive heterochromatic (dark) bands. We carried out morphometric measurements of high-resolution chromosome ideograms for the first time to characterize the total euchromatic and heterochromatic chromosome band length, distribution and localization of 20,145 known protein-coding genes, 790 recognized autism spectrum disorder (ASD) genes and 365 obesity genes. The individual lengths of G-negative euchromatin and G-positive heterochromatin chromosome bands were measured in millimeters and recorded from scaled and stacked digital images of 850-band high-resolution ideograms supplied by the International Society of Chromosome Nomenclature (ISCN) 2013. Our overall measurements followed established banding patterns based on chromosome size. G-negative euchromatic band regions contained 60% of protein-coding genes while the remaining 40% were distributed across the four heterochromatic dark band sub-types. ASD genes were disproportionately overrepresented in the darker heterochromatic sub-bands, while the obesity gene distribution pattern did not significantly differ from protein-coding genes. Our study supports recent trends implicating genes located in heterochromatin regions playing a role in biological processes including neurodevelopment and function, specifically genes associated with ASD.

Impact of Social Networking Sites on Children in Military Families

Youth in military families experience a relatively unique set of stressors that can put them at risk for numerous psychological and behavior problems. Thus, there is a need to identify potential mechanisms by which children can gain resiliency against these stressors. One potential mechanism that has yet to be empirically studied with military youth is social networking sites (SNSs). SNSs have gained significant popularity among society, especially youth. Given the significance of these communication tools in youths’ lives, it is important to analyze how SNS use may affect military youth and their ability to cope with common military life stressors. The current review examines the potential positive and negative consequences associated with SNS use in coping with three common stressors of youth in military families: parent deployment, frequent relocation, and having a family member with a psychological or physical disability. By drawing from SNS and military literature, we predict that SNS use can be a positive tool for helping children in military families to cope with stressors. However, certain SNS behaviors can potentially result in more negative outcomes. Recommendations for future research are also discussed.

A Multilevel Meta-analysis on Academic Achievement Among Maltreated Youth

Maltreatment can influence normative development and negatively impact emotional, behavioral, and social functioning in youth. As a result, it is not surprising that maltreated youth, as compared to non-maltreated youth, tend to underperform academically. Research on the academic performance of maltreated youth has increased over the last decade and several review papers have been published in this area. While the conclusions of these review articles have been that maltreated youth are at greater risk for academic deficits as compared to their non-maltreated peers, there are several conflicting findings within the literature that make it difficult to determine if or to what extent maltreated youth may demonstrate academic difficulty. Using a multilevel, structural equation model meta-analysis technique, the current study sought to provide a quantitative synthesis of the literature by examining the mean difference between maltreated and non-maltreated youth on measures of academic performance. Moreover, the current study also examined group differences between academic subject and maltreatment type. A total of 72 effect sizes were extracted from 32 studies that met inclusion criteria. Results demonstrated an overall negative, medium effect size, such that maltreated youth tended to perform slightly greater than half a standard deviation below non-maltreated youth on measures of academic performance. Moderation analyses suggest deficits may be greater on measures of general academic performance, as compared to language arts measures. No differences were observed for maltreatment type. These findings highlight the need for increased focus on academic difficulties among maltreated youth.

The relation between dimensions of maltreatment, placement instability, and mental health among youth in foster care

Youth in foster care with maltreatment experiences often demonstrate higher rates of mental and behavioral health problems compared to youth in the general population as well as maltreated youth who remain at home. Previous research has demonstrated that dimensions of maltreatment (type, frequency, and severity) and placement instability are two prominent factors that account for high rates of psychopathology (e.g., depression, anxiety, and disruptive behavior disorders). The present study sought to clarify the relation between maltreatment and mental health among youth in foster care by studying both the isolated dimensions of maltreatment and cumulative maltreatment, and to determine whether the effects of maltreatment on mental health operated indirectly through placement instability. Information on youth in foster cares (N = 496, Mage = 13.14) mental and behavioral health, maltreatment history, and placement changes were obtained from state records and primary caregivers. Using a SEM framework, the results suggest that maltreatment and placement instability each independently relate to mental and behavioral health problems. Further, none of the maltreatment types predicted greater placement instability in the current models. These findings suggest that placement stability is critical for mental health for youth in foster care, regardless of the type, severity, or frequency of their maltreatment experiences. Results also indicated that, although cumulative maltreatment predicted both internalizing and externalizing symptoms, maltreatment frequency and severity had direct relations to externalizing symptoms only. These findings underscore the utility of comprehensive maltreatment assessment, encouraging researchers and clinicians to assess and carefully consider the relation between maltreatment dimensions and outcomes.

Dimensions of maltreatment and academic outcomes for youth in foster care

Childhood maltreatment is often associated with youths ability to successfully function in school. Youth with a history of maltreatment often receive lower grades and scores on tests of academic achievement, as well as demonstrate more negative behaviors in school, as compared to non-maltreated youth. However, there are many inconsistencies in previous studies examining the association between maltreatment and academic outcomes in youth. One potential reason for mixed findings within the literature could be a result of how maltreatment is measured and operationalized. The current study examined if the methods used to define and describe maltreatment contribute to the association between maltreatment and academic functioning in youth. Youth in foster care (N = 490, Mage = 13.13[3.09]) were recruited and information on their maltreatment history and academic functioning was obtained from official agencies, school records, and self-reported measures. Using a SEM framework when examining each dimension separately in the same model, results suggested that frequency maltreatment was more predictive of academic behavior, as compared to type and severity. No dimensions were associated with grades and significant findings were only observed for models using self-report data. However, when examined using a measurement model approach, maltreatment as a whole was associated with school behavior, which was found for both self-report and case file measurement models. The findings suggest a need for research on academic functioning to take a comprehensive approach when measuring and defining maltreatment as this may be a more robust and accurate predictor of academic functioning.