Implications of comorbidity and ascertainment bias for identifying disease genes

Gene copy number variation and pediatric mental health/neurodevelopment in a general population

We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health and cognition in a community sample of 7100 unrelated children and youth of European or East Asian ancestry (Spit for Science). Clinically significant or susceptibility CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of attention-deficit/hyperactivity disorder (ADHD) traits (P = 5.0 × 10-3), longer response inhibition (a cognitive deficit found in several mental health and neurodevelopmental disorders; P = 1.0 × 10-2) and increased prevalence of mental health diagnoses (P = 1.9 × 10-6, odds ratio: 3.09), specifically ADHD, autism spectrum disorder anxiety and learning problems/learning disorder (P's < 0.01). There was an increased burden of rare deletions in gene-sets related to brain function or expression in brain associated with more ADHD traits. With the current mental health crisis, our data established a baseline for delineating genetic contributors in pediatric-onset conditions.

Hypothesis-driven genome-wide association studies provide novel insights into genetics of reading disabilities

Reading Disability (RD) is often characterized by difficulties in the phonology of the language. While the molecular mechanisms underlying it are largely undetermined, loci are being revealed by genome-wide association studies (GWAS). In a previous GWAS for word reading (Price, 2020), we observed that top single-nucleotide polymorphisms (SNPs) were located near to or in genes involved in neuronal migration/axon guidance (NM/AG) or loci implicated in autism spectrum disorder (ASD). A prominent theory of RD etiology posits that it involves disturbed neuronal migration, while potential links between RD-ASD have not been extensively investigated. To improve power to identify associated loci, we up-weighted variants involved in NM/AG or ASD, separately, and performed a new Hypothesis-Driven (HD)-GWAS. The approach was applied to a Toronto RD sample and a meta-analysis of the GenLang Consortium. For the Toronto sample (n = 624), no SNPs reached significance; however, by gene-set analysis, the joint contribution of ASD-related genes passed the threshold (p~1.45 × 10-2, threshold = 2.5 × 10-2). For the GenLang Cohort (n = 26,558), SNPs in DOCK7 and CDH4 showed significant association for the NM/AG hypothesis (sFDR q = 1.02 × 10-2). To make the GenLang dataset more similar to Toronto, we repeated the analysis restricting to samples selected for reading/language deficits (n = 4152). In this GenLang selected subset, we found significant association for a locus intergenic between BTG3-C21orf91 for both hypotheses (sFDR q < 9.00 × 10-4). This study contributes candidate loci to the genetics of word reading. Data also suggest that, although different variants may be involved, alleles implicated in ASD risk may be found in the same genes as those implicated in word reading. This finding is limited to the Toronto sample suggesting that ascertainment influences genetic associations.

Convergence and Divergence of Rare Genetic Disorders on Brain Phenotypes: A Review

IMPORTANCE

Rare genetic disorders modulating gene expression-as exemplified by gene dosage disorders (GDDs)-represent a collectively common set of high-risk factors for neuropsychiatric illness. Research on GDDs is rapidly expanding because these variants have high effect sizes and a known genetic basis. Moreover, the prevalence of recurrent GDDs (encompassing aneuploidies and certain copy number variations) enables genetic-first phenotypic characterization of the same GDD across multiple individuals, thereby offering a unique window into genetic influences on the human brain and behavior. However, the rapid growth of GDD research has unveiled perplexing phenotypic convergences and divergences across genomic loci; while phenotypic profiles may be specifically associated with a genomic variant, individual behavioral and neuroimaging traits appear to be nonspecifically influenced by most GDDs.

OBSERVATIONS

This complexity is addressed by (1) providing an accessible survey of genotype-phenotype mappings across different GDDs, focusing on psychopathology, cognition, and brain anatomy, and (2) detailing both methodological and mechanistic sources for observed phenotypic convergences and divergences. This effort yields methodological recommendations for future comparative phenotypic research on GDDs as well as a set of new testable hypotheses regarding aspects of early brain patterning that might govern the complex mapping of genetic risk onto phenotypic variation in neuropsychiatric disorders.

CONCLUSIONS AND RELEVANCE

A roadmap is provided to boost accurate measurement and mechanistic interrogation of phenotypic convergence and divergence across multiple GDDs. Pursuing the questions posed by GDDs could substantially improve our taxonomical, neurobiological, and translational understanding of neuropsychiatric illness.

Pleiotropy and Cross-Disorder Genetics Among Psychiatric Disorders

Genome-wide analyses of common and rare genetic variations have documented the heritability of major psychiatric disorders, established their highly polygenic genetic architecture, and identified hundreds of contributing variants. In recent years, these studies have illuminated another key feature of the genetic basis of psychiatric disorders: the important role and pervasive nature of pleiotropy. It is now clear that a substantial fraction of genetic influences on psychopathology transcend clinical diagnostic boundaries. In this review, we summarize evidence in psychiatry for pleiotropy at multiple levels of analysis: from overall genome-wide correlation to biological pathways and down to the level of individual loci. We examine underlying mechanisms of observed pleiotropy, including genetic effects on neurodevelopment, diverse actions of regulatory elements, mediated effects, and spurious associations of genomic variation with multiple phenotypes. We conclude with an exploration of the implications of pleiotropy for understanding the genetic basis of psychiatric disorders, informing nosology, and advancing the aims of precision psychiatry and genomic medicine.

Patterns and predictors of opioid use among migraine patients at emergency departments: A retrospective database analysis

Objectives

To compare medication use and health resource utilization between migraineurs with evidence of opioid use at emergency department visit versus no opioid use at emergency department visit, and to examine predictors of opioid use among migraineurs at emergency department visits.

Methods

This was a retrospective study using REACHnet electronic health records (December 2013 to April 2017) from Baylor Scott & White Health Plan. The index date was defined as the first migraine-related emergency department visit after ≥6 months of enrollment. Adult patients with a migraine diagnosis and ≥6 months of continuous enrollment before and after their index dates were included. Descriptive statistics and bivariate analyses were used to compare medication use and health resource utilization between opioid users and non-opioid users. Multivariable logistic regression was used to examine predictors of opioid use at emergency department visits.

Results

A total of 788 migraineurs met eligibility criteria. Over one-third (n = 283, 35.9%) received ≥1 opioid medication during their index date emergency department visit. Morphine (n = 103, 13.1%) and hydromorphone (n = 85, 10.8%) were the most frequently used opioids. Opioid users had more hospitalizations and emergency department visits during their pre-index period (both p < 0.05). Significant ( p < 0.05) predictors of opioid use at emergency department visits included past migraine-related opioid use (2–4 prescriptions, Odds Ratio = 1.66; 5–9 prescriptions, Odds Ratio = 2.12; ≥10 prescriptions, Odds Ratio = 4.43), past non-migraine-related opioid use (≥10 prescriptions, Odds Ratio = 1.93), past emergency department visits (1–3 visits, Odds Ratio = 1.84), age (45–64 years, Odds Ratio = 1.45), and sleep disorder (Odds Ratio = 1.43), controlling for covariates.

Conclusion

Opioids were commonly given to migraineurs at emergency departments. Previous opioid use, health resource utilization, age, and specific comorbidities might be used to identify migraineurs with a high risk of opioid use.

Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders

Many neuropsychiatric disorders exhibit differences in prevalence, age of onset, symptoms or course of illness between males and females. For the most part, the origins of these differences are not well understood. In this article, we provide an overview of sex differences in psychiatric disorders including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), anxiety, depression, alcohol and substance abuse, schizophrenia, eating disorders and risk of suicide. We discuss both genetic and nongenetic mechanisms that have been hypothesized to underlie these differences, including ascertainment bias, environmental stressors, X‐ or Y‐linked risk loci, and differential liability thresholds in males and females. We then review the use of twin, family and genome‐wide association approaches to study potential genetic mechanisms of sex differences and the extent to which these designs have been employed in studies of psychiatric disorders. We describe the utility of genetic epidemiologic study designs, including classical twin and family studies, large‐scale studies of population registries, derived recurrence risks, and molecular genetic analyses of genome‐wide variation that may enhance our understanding sex differences in neuropsychiatric disorders.

Examining sex differences in pleiotropic effects for depression and smoking using polygenic and gene-region aggregation techniques

Sex differences in rates of depression are thought to contribute to sex differences in smoking initiation (SI) and number of cigarettes smoked per day (CPD). One hypothesis is that women smoke as a strategy to cope with anxiety and depression, and have difficulty quitting because of concomitant changes in hypothalamic-pituitary-adrenocortical (HPA) axis function during nicotine withdrawal states. Despite evidence of biological ties, research has not examined whether genetic factors that contribute to depression-smoking comorbidity differ by sex. We utilized two statistical aggregation techniques-polygenic scores (PGSs) and sequence kernel association testing-to assess the degree of pleiotropy between these behaviors and moderation by sex in the Health and Retirement Study (N = 8,086). At the genome-wide level, we observed associations between PGSs for depressive symptoms and SI, and measured SI and depressive symptoms (all p < .01). At the gene level, we found evidence of pleiotropy in FKBP5 for SI (p = .028), and sex-specific pleiotropy in females in NR3C2 (p = .030) and CHRNA5 (p = .025) for SI and CPD, respectively. Results suggest bidirectional associations between depression and smoking may be partially accounted for by shared genetic factors, and genetic variation in genes related to HPA-axis functioning and nicotine dependence may contribute to sex differences in SI and CPD.

Identification of Pleiotropic Cancer Susceptibility Variants from Genome-Wide Association Studies Reveals Functional Characteristics

Background: There exists compelling evidence that some genetic variants are associated with the risk of multiple cancer sites (i.e., pleiotropy). However, the biological mechanisms through which the pleiotropic variants operate are unclear.Methods: We obtained all cancer risk associations from the National Human Genome Research Institute-European Bioinformatics Institute GWAS Catalog, and correlated cancer risk variants were clustered into groups. Pleiotropic variant groups and genes were functionally annotated. Associations of pleiotropic cancer risk variants with noncancer traits were also obtained.Results: We identified 1,431 associations between variants and cancer risk, comprised of 989 unique variants associated with 27 unique cancer sites. We found 20 pleiotropic variant groups (2.1%) composed of 33 variants (3.3%), including novel pleiotropic variants rs3777204 and rs56219066 located in the ELL2 gene. Relative to single-cancer risk variants, pleiotropic variants were more likely to be in genes (89.0% vs. 65.3%, P = 2.2 × 10-16), and to have somewhat larger risk allele frequencies (median RAF = 0.49 versus 0.39, P = 0.046). The 27 genes to which the pleiotropic variants mapped were suggestive for enrichment in response to radiation and hypoxia, alpha-linolenic acid metabolism, cell cycle, and extension of telomeres. In addition, we observed that 8 of 33 pleiotropic cancer risk variants were associated with 16 traits other than cancer.Conclusions: This study identified and functionally characterized genetic variants showing pleiotropy for cancer risk.Impact: Our findings suggest biological pathways common to different cancers and other diseases, and provide a basis for the study of genetic testing for multiple cancers and repurposing cancer treatments. Cancer Epidemiol Biomarkers Prev; 27(1); 75-85. ©2017 AACR.

A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases

There is growing evidence of shared risk alleles between complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing between all individuals (whole-group pleiotropy), or a subset of individuals within a genetically heterogeneous cohort (subgroup heterogeneity). BUHMBOX is a well-powered statistic distinguishing between these two situations using genotype data. We observed a shared genetic basis between 11 autoimmune diseases and type 1 diabetes (T1D, p<10⁻⁴), and 11 autoimmune diseases and rheumatoid arthritis (RA, p<10⁻³). This sharing was not explained by subgroup heterogeneity (corrected p_BUHMBOX>0.2, 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (p<10⁻⁹) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (p_BUHMBOX=0.008, 2,406 seronegative RA cases). We also observed a shared genetic basis between major depressive disorder (MDD) and schizophrenia (p<10⁻⁴) that was not explained by subgroup heterogeneity (p_BUHMBOX=0.28 in 9,238 MDD cases).

Implications of pleiotropy: challenges and opportunities for mining Big Data in biomedicine

Pleiotropy arises when a locus influences multiple traits. Rich GWAS findings of various traits in the past decade reveal many examples of this phenomenon, suggesting the wide existence of pleiotropic effects. What underlies this phenomenon is the biological connection among seemingly unrelated traits/diseases. Characterizing the molecular mechanisms of pleiotropy not only helps to explain the relationship between diseases, but may also contribute to novel insights concerning the pathological mechanism of each specific disease, leading to better disease prevention, diagnosis and treatment. However, most pleiotropic effects remain elusive because their functional roles have not been systematically examined. A systematic investigation requires availability of qualified measurements at multilayered biological processes (e.g., transcription and translation). The rise of Big Data in biomedicine, such as high-quality multi-omics data, biomedical imaging data and electronic medical records of patients, offers us an unprecedented opportunity to investigate pleiotropy. There will be a great need of computationally efficient and statistically rigorous methods for integrative analysis of these Big Data in biomedicine. In this review, we outline many opportunities and challenges in methodology developments for systematic analysis of pleiotropy, and highlight its implications on disease prevention, diagnosis and treatment.

Deriving comorbidities from medical records using natural language processing

Extracting comorbidity information is crucial for phenotypic studies because of the confounding effect of comorbidities. We developed an automated method that accurately determines comorbidities from electronic medical records. Using a modified version of the Charlson comorbidity index (CCI), two physicians created a reference standard of comorbidities by manual review of 100 admission notes. We processed the notes using the MedLEE natural language processing system, and wrote queries to extract comorbidities automatically from its structured output. Interrater agreement for the reference set was very high (97.7%). Our method yielded an F1 score of 0.761 and the summed CCI score was not different from the reference standard (p=0.329, power 80.4%). In comparison, obtaining comorbidities from claims data yielded an F1 score of 0.741, due to lower sensitivity (66.1%). Because CCI has previously been validated as a predictor of mortality and readmission, our method could allow automated prediction of these outcomes.

Disorders and borders: psychiatric genetics and nosology

Over the past century, the definition and classification of psychiatric disorders has evolved through a combination of historical trends, clinical observations, and empirical research. The current nosology, instantiated in the DSM-5 and ICD-10, rests on descriptive criteria agreed upon by a consensus of experts. While the development of explicit criteria has enhanced the reliability of diagnosis, the validity of the current diagnostic categories has been the subject of debate and controversy. Genetic studies have long been regarded as a key resource for validating the boundaries among diagnostic categories. Genetic epidemiologic studies have documented the familiality and heritability of clinically defined psychiatric disorders and molecular genetic studies have begun to identify specific susceptibility variants. At the same time, there is growing evidence from family, twin and genomic studies that genetic influences on psychiatric disorders transcend clinical boundaries. Here I review this evidence for cross-disorder genetic effects and discuss the implications of these findings for psychiatric nosology. Psychiatric genetic research can inform a bottom-up reappraisal of psychopathology that may help the field move beyond a purely descriptive classification and toward an etiology-based nosology.

Pleiotropy in complex traits: challenges and strategies

Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.

Examining and interpreting the female protective effect against autistic behavior

Male preponderance in autistic behavioral impairment has been explained in terms of a hypothetical protective effect of female sex, yet little research has tested this hypothesis empirically. If females are protected, they should require greater etiologic load to manifest the same degree of impairment as males. The objective of this analysis was to examine whether greater familial etiologic load was associated with quantitative autistic impairments in females compared with males. Subjects included 3,842 dizygotic twin pairs from the Twins Early Development Study (TEDS) and 6,040 dizygotic twin pairs from the Child and Adolescent Twin Study of Sweden (CATSS). In both samples, we compared sibling autistic traits between female and male probands, who were identified as children scoring in the top 90th and 95th percentiles of the population autistic trait distributions. In both TEDS and CATSS, siblings of female probands above the 90th percentile had significantly more autistic impairments than the siblings of male probands above the 90th percentile. The siblings of female probands above the 90th percentile also had greater categorical recurrence risk in both TEDS and CATSS. Results were similar in probands above the 95th percentile. This finding, replicated across two nationally-representative samples, suggests that female sex protects girls from autistic impairments and that girls may require greater familial etiologic load to manifest the phenotype. It provides empirical support for the hypothesis of a female protective effect against autistic behavior and can be used to inform and interpret future gene finding efforts in autism spectrum disorders.

Bringing a developmental perspective to anxiety genetics

Despite substantial recent advancements in psychiatric genetic research, progress in identifying the genetic basis of anxiety disorders has been limited. We review the candidate gene and genome-wide literatures in anxiety, which have made limited progress to date. We discuss several reasons for this hindered progress, including small samples sizes, heterogeneity, complicated comorbidity profiles, and blurred lines between normative and pathological anxiety. To address many of these challenges, we suggest a developmental, multivariate framework that can inform and enhance anxiety phenotypes for genetic research. We review the psychiatric and genetic epidemiological evidence that supports such a framework, including the early onset and chronic course of anxiety disorders, shared genetic risk factors among disorders both within and across time, and developmentally dynamic genetic influences. We propose three strategies for developmentally sensitive phenotyping: examination of early temperamental risk factors, use of latent factors to model underlying anxiety liability, and use of developmental trajectories as phenotypes. Expanding the range of phenotypic approaches will be important for advancing studies of the genetic architecture of anxiety disorders.

How reliable is depression screening in alcohol and drug users? A validation of brief and ultra-brief questionnaires

BACKGROUND

Depression is highly comorbid with alcohol and drug problems, resulting in greater impairment, reduced treatment adherence and poor outcomes. Little evidence exists to support the use of mental health screening tools in routine addiction treatment. This study tested the validity and reliability of PHQ-9 and PHQ-2 as depression case finding tools in an outpatient drug treatment sample in the United Kingdom.

METHODS

A sample of 103 patients took part in diagnostic assessments using CIS-R and completed brief screening questionnaires. A subgroup of 60 patients completed retests after 4 weeks. Diagnostic results were compared to brief measures using receiver operating characteristic (ROC) curves. Psychometric properties were also calculated to evaluate the validity and reliability of self-completed questionnaires.

RESULTS

A PHQ-9 score ≥ 12 had a sensitivity of 81% and specificity of 75% for major depression, also displaying good retest reliability (intra-class correlation, 0.78) and internal consistency (Cronbach's alpha, 0.84). PHQ-2 had 68% sensitivity and 70% specificity, with more modest retest reliability (0.66) and internal consistency (0.64).

LIMITATIONS

Diagnostic interviews did not consider the temporal sequencing of the onset of drug use and mental health problems.

CONCLUSIONS

PHQ-9 is a valid and reliable depression screening tool for drug and alcohol users. The brevity and ease of administration of self-completed questionnaires make them useful clinical tools in addiction services commonly encountering a high prevalence of depression.

On the adjustment for covariates in genetic association analysis: a novel, simple principle to infer direct causal effects

In genetic association studies, different complex phenotypes are often associated with the same marker. Such associations can be indicative of pleiotropy (i.e. common genetic causes), of indirect genetic effects via one of these phenotypes, or can be solely attributable to non-genetic/environmental links between the traits. To identify the phenotypes with the inducing genetic association, statistical methodology is needed that is able to distinguish between the different causes of the genetic associations. Here, we propose a simple, general adjustment principle that can be incorporated into many standard genetic association tests which are then able to infer whether an SNP has a direct biological influence on a given trait other than through the SNP's influence on another correlated phenotype. Using simulation studies, we show that, in the presence of a non-marker related link between phenotypes, standard association tests without the proposed adjustment can be biased. In contrast to that, the proposed methodology remains unbiased. Its achieved power levels are identical to those of standard adjustment methods, making the adjustment principle universally applicable in genetic association studies. The principle is illustrated by an application to three genome-wide association analyses.

Investigation of variation in SNAP-25 and ADHD and relationship to co-morbid major depressive disorder

Synaptosomal-associated protein of 25 kDa (SNAP-25), a protein involved in presynaptic neurotransmitter release, is a candidate gene for attention deficit/hyperactivity disorder (ADHD). Previous investigators have reported association initially with two single nucleotide polymorphisms (SNPs) (rs3746544, rs1051312) and their associated haplotypes. Subsequently, additional SNPs across the region were also reported to be associated with ADHD. We attempted to replicate these observations in a sample of 229 families with ADHD offspring by genotyping 61 SNPs spanning the region containing SNAP-25. A single SNP (rs3787283) which is in strong linkage disequilibrium (LD) with rs3746544 and rs1051312 (D' = 0.89-0.94) resulted in a nominally significant association (P = 0.002). When we pooled our data with those from prior studies, results were modestly significant for rs3746544 (P = 0.048) and rs6077690 (P = 0.031). As an attempt to determine if specific ADHD-related phenotypes may be more relevant to SNAP-25 than the categorical diagnosis, we carried out exploratory subgroup analysis in our ADHD sample according to co-morbid status. We found the strongest association result in the ADHD patients with co-morbid major depressive disorder (MDD). Six SNPs were nominally associated with the ADHD and co-morbid MDD cases (P = 0.012-0.045). Furthermore, a haplotype block located 11 kb 3' of the gene showed positive evidence for association with this phenotype (global P = 0.013). In conclusion, we report some evidence supporting the association of previously implicated SNPs (rs3746544, rs1051312) of SNAP-25 to ADHD. We further suggest that co-morbidity with MDD may enhance detection of the association between SNAP-25 and ADHD.

Epidemiology of specific phobia subtypes: findings from the Dresden Mental Health Study

This study determined the prevalence, age of onset, comorbidity, and impairment associated with specific phobia subtypes in the community. Data were drawn from the Dresden Mental Health Study (N=2064), a representative community-based sample of young women in Dresden, Germany. The lifetime prevalence of any specific phobia was 12.8%, with subtypes ranging in prevalence between 0.2% (vomiting, infections) and 5.0% (animals). There were significant differences in the mean age of onset of specific phobias. Significant differences in comorbidity patterns also emerged between subtypes. No significant differences were found in level of impairment associated with the subtypes. The findings suggest that specific phobias are common among young women and that they differ in prevalence, associated comorbidity, and mean age of onset. These data suggest significant differences in the phenomenology and clinical significance of specific phobia subtypes.

Haplotype association between GABAA receptor gamma2 subunit gene (GABRG2) and methamphetamine use disorder

Psychostimulant use disorder and schizophrenia have a substantial genetic basis. Evidence from human and animal studies on the involvement of the gamma-aminobutyric acid (GABA) system in methamphetamine (METH) use disorder and schizophrenia is mounting. As we tested for the association of the human GABA(A) receptor gamma 2 subunit gene (GABRG2) with each diagnostic group, we used a case-control design with a set of 178 subjects with METH use disorder, 288 schizophrenics and 288 controls. First, we screened 96 controls and identified six SNPs in GABRG2, three of whom we newly reported. Next, we selected two SNPs, 315C>T and 1128+99C>A, as representatives of the linkage disequilibrium blocks for further case-control association analysis. Although no associations were found in either allelic or genotypic frequencies, we detected a haplotypic association in GABRG2 with METH use disorder, but not with schizophrenia. This finding partly replicates a recent case-control study of GABRG2 in METH use disorder, and thus indicates that GABRG2 may be one of the susceptibility genes of METH use disorder.

Covariate adjustment in family-based association studies

Family-based tests of association between a candidate locus and a disease evaluate how often a variant allele at the locus is transmitted from parents to offspring. These tests assume that in the absence of association, an affected offspring is equally likely to have inherited either one of the two homologous alleles carried by a parent. However, transmission distortion was documented in families in which the offspring are unselected for phenotype. Moreover, if offspring genotypes are associated with a risk factor for the disease, transmission distortion to affected offspring can occur in the absence of a causal relation between gene and disease risk. We discuss the appropriateness of adjusting for established risk factors when evaluating association in family-based studies. We present methods for adjusting the transmission/disequilibrium test for risk factors when warranted, and we apply them to data on CYP19 (aromatase) genotypes in nuclear families with multiple cases of breast cancer. Simulations show that when genotypes are correlated with risk factors, the unadjusted test statistics have inflated size, while the adjusted ones do not. The covariate-adjusted tests are less powerful than the unadjusted ones, suggesting the need to check the relationship between genotypes and known risk factors to verify that adjustment is needed. The adjusted tests are most useful for data containing a large proportion of families that lack disease-discordant sibships, i.e., data for which multiple logistic regression of matched sibships would have little power. Software for performing the covariate-adjusted tests is available at http://www.stanford.edu/dept/HRP/epidemiology/COVTDT.

Sensorineural hearing loss in children and adults with Williams syndrome

Williams syndrome (WS) is a genetic neurodevelopmental disorder, most often accompanied by mild-to-moderate mental retardation. Individuals with WS show unique communication strengths and impairments that are challenging to treat in community, educational, and vocational settings. Many issues regarding characteristics of auditory sensitivity in WS remain to be resolved. Our purpose was to obtain behavioral (screening and pure-tone audiometry) and objective (distortion product otoacoustic emission-DPOAE) measures of auditory system function from a group of 27 individuals with WS, 6-48 years of age. These measures were gathered both at an international professional conference (n = 19) and in a clinic setting (n = 8). In the behavioral screening conditions, 16/19 (84%) of the individuals failed the hearing screening; and in the behavioral diagnostic hearing condition, 6/8 (75%) demonstrated sensorineural hearing loss (SNHL) and 1/8 demonstrated a hearing loss of undetermined type. In the objective DPOAE testing, 19/25 (76%) had DPOAE absolute amplitudes below the 5th percentile for ears with normal hearing [Gorga et al. (1997); Ear Hear 18(6):440-455]. We report SNHL in 14/18 (78%) of school-age children with WS. Post hoc analyses revealed a significant effect for age, suggesting a pattern of progressive hearing loss. An effect size analysis indicated a clinically meaningful difference in the hearing sensitivity between school-aged children and adults in the high frequencies (4,000 and 8,000 Hz). Similar hearing loss phenotype was observed in patients with familial nonsyndromic supravalvular aortic stenosis (SVAS), suggesting that molecular defects in the elastin gene in the pathogenesis of SNHL in WS. This study highlights the importance of early and regular hearing testing for WS patients and suggests that elastin may have a previously unappreciated function in maintaining hearing sensitivity.

Serotonin transporter gene functional polymorphism: a plausible candidate gene for increased vascular risk in depression

The evidence of increased vascular morbidity and mortality associated with depression has generated research interest in studying the mechanisms or causal pathways underlying this association. Recent advances in molecular genetics have demonstrated that serotonin transporter gene functional polymorphism may confer susceptibility for affective disorder as well as for some cardiovascular risk factors. Taking into account these genetic findings, this article proposes a hypothesis that serotonin transporter gene functional polymorphism may be a plausible candidate gene to study the genetic mechanisms of depression-related increased vascular morbidity and mortality. Future research projects to test this hypothesis is warranted.

Marijuana use among adolescents

More than half of US adolescents will experiment with marijuana. Of those who try marijuana more than once, approximately one third will subsequently use marijuana regularly, although most will have stopped by their late 20s. Although genetic predisposition plays the most important role in determining who will develop dependence, environmental factors influence who will initiate marijuana use. One of the challenges for prevention and treatment programs is that the immediate adverse effects of marijuana use are not extreme, and many adolescents have difficulty in making decisions based on future risks. Therefore, the consequences of leaving school early, having unprotected sex, and driving while intoxicated are often insufficient to deter adolescents from using marijuana. Thus, it is not surprising that current prevention and treatment programs have had limited success in decreasing the rates of initiation and regular use of marijuana among adolescents. However, the accumulation of data about marijuana use in adolescents has the potential to enable the development of more effective prevention and treatment programs.

On the validity of the TDT test in the presence of comorbidity and ascertainment bias

Comorbidity, the association of two disorders, occurs commonly with complex diseases. In this paper, we investigate the effects of both true (within-family) comorbidity and spurious comorbidity due to ascertainment bias on the validity of both the parental and sibling control transmission/disequilibrium test. Specifically, we consider settings in which a candidate gene is unlinked to the target phenotype but is in linkage disequilibrium with a comorbid phenotype. We derive conditions under which the presence of true and/or spurious comorbidity will result in an artificial correlation between the target phenotype and the candidate gene.