Family-based Sample Research Articles

The importance of family-based sampling for biobanks.

Biobanks aim to improve our understanding of health and disease by collecting and analysing diverse biological and phenotypic information in large samples. So far, biobanks have largely pursued a population-based sampling strategy, where the individual is the unit of sampling, and familial relatedness occurs sporadically and by chance. This strategy has been remarkably efficient and successful, leading to thousands of scientific discoveries across multiple research domains, and plans for the next wave of biobanks are underway. In this Perspective, we discuss the strengths and limitations of a complementary sampling strategy for future biobanks based on oversampling of close genetic relatives. Such family-based samples facilitate research that clarifies causal relationships between putative risk factors and outcomes, particularly in estimates of genetic effects, because they enable analyses that reduce or eliminate confounding due to familial and demographic factors. Family-based biobank samples would also shed new light on fundamental questions across multiple fields that are often difficult to explore in population-based samples. Despite the potential for higher costs and greater analytical complexity, the many advantages of family-based samples should often outweigh their potential challenges.

Genetic architecture and socio-environmental risk factors for major depressive disorder in Nepal.

Major depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations. This study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples. We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18-0.34, p = 8.5 × 10-6). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI -0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06-0.08), female sex (beta = 0.160, 95% CI 0.15-0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03-0.07), while neither the depression PGS (beta = 0.004, 95% CI -0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI -0.01 to 0.03) were strongly associated with MDD. Estimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.

Genetic correlations between liver fat content, metabolic health, and adiposity distribution in the Fels Longitudinal Study

Background and aimsHepatic steatosis is known to be heritable, but its genetic basis is mostly uncharacterized. Steatosis is associated with metabolic and adiposity features; recent studies hypothesize that shared genetic effects between these traits could account for some of the unexplained heritability. This study aimed to quantify these genetic associations in a family-based sample of non-Hispanic white adults. Methods and results704 participants (18–95 years, 55.8% female) from the Fels Longitudinal Study with an MRI assessment of liver fat were included. Quantitative genetic analyses estimated the age- and sex-adjusted heritability of individual traits and the genetic correlations within trait pairs. Mean liver fat was 5.95% (SE = 0.23) and steatosis (liver fat >5.56%) was present in 29.8% of participants. Heritability (h2± SE) of steatosis was 0.72 ± 0.17 (p = 6.80e−6). All other traits including liver enzymes, fasting glucose, HOMA-IR, visceral and subcutaneous adipose tissue (VAT, SAT), body mass index, body fat percent, waist circumference, lipids and blood pressure were also heritable. Significant genetic correlations were found between liver fat and all traits except aspartate aminotransferase (AST), and among most trait pairs. Highest genetic correlations were between liver fat and HOMA-IR (0.85 ± 0.08, p = 1.73e−8), fasting glucose and ALT (0.89 ± 0.26, p = 6.68e−5), and HOMA-IR with: waist circumference (0.81 ± 0.12, p = 3.76e−6), body fat percent (0.78 ± 0.12 p = 2.42e−5) and VAT (0.73 ± 0.07, p = 6.37e−8). ConclusionsCommon genes may exist between liver fat accumulation, metabolic features and adiposity phenotypes.

The production of within-family inequality: Insights and implications of integrating genetic data.

The integration of genetic data within large-scale social and health surveys provides new opportunities to test long-standing theories of parental investments in children and within-family inequality. Genetic predictors, called polygenic scores, allow novel assessments of young children's abilities that are uncontaminated by parental investments, and family-based samples allow indirect tests of whether children's abilities are reinforced or compensated. We use over 16,000 sibling pairs from the UK Biobank to test whether the relative ranking of siblings' polygenic scores for educational attainment is consequential for actual attainments. We find evidence consistent with compensatory processes, on average, where the association between genotype and phenotype of educational attainment is reduced by over 20% for the higher-ranked sibling compared to the lower-ranked sibling. These effects are most pronounced in high socioeconomic status areas. We find no evidence that similar processes hold in the case of height or for relatives who are not full biological siblings (e.g. cousins). Our results provide a new use of polygenic scores to understand processes that generate within-family inequalities and also suggest important caveats to causal interpretations the effects of polygenic scores using sibling difference designs. Future work should seek to replicate these findings in other data and contexts.

A family-based study of genetic and epigenetic effects across multiple neurocognitive, motor, social-cognitive and social-behavioral functions

Many psychiatric and neurodevelopmental disorders are known to be heritable, but studies trying to elucidate the genetic architecture of such traits often lag behind studies of somatic traits and diseases. The reasons as to why relatively few genome-wide significant associations have been reported for such traits have to do with the sample sizes needed for the detection of small effects, the difficulty in defining and characterizing the phenotypes, partially due to overlaps in affected underlying domains (which is especially true for cognitive phenotypes), and the complex genetic architectures of the phenotypes, which are not wholly captured in traditional case–control GWAS designs. We aimed to tackle the last two issues by performing GWASs of eight quantitative neurocognitive, motor, social-cognitive and social-behavioral traits, which may be considered endophenotypes for a variety of psychiatric and neurodevelopmental conditions, and for which we employed models capturing both general genetic association and parent-of-origin effects, in a family-based sample comprising 402 children and their parents (mostly family trios). We identified 48 genome-wide significant associations across several traits, of which 3 also survived our strict study-wide quality criteria. We additionally performed a functional annotation of implicated genes, as most of the 48 associations were with variants within protein-coding genes. In total, our study highlighted associations with five genes (TGM3, CACNB4, ANKS1B, CSMD1 and SYNE1) associated with measures of working memory, processing speed and social behavior. Our results thus identify novel associations, including previously unreported parent-of-origin associations with relevant genes, and our top results illustrate new potential gene → endophenotype → disorder pathways.

NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches.

Included in the neurotrophins family, the Neuritin 1 gene (NRN1) has emerged as an attractive candidate gene for schizophrenia (SZ) since it has been associated with the risk for the disorder and general cognitive performance. In this work, we aimed to further investigate the association of NRN1 with SZ by exploring its role on age at onset and its brain activity correlates. First, we developed two genetic association analyses using a family-based sample (80 early-onset (EO) trios (offspring onset ≤ 18 years) and 71 adult-onset (AO) trios) and an independent case–control sample (120 healthy subjects (HS), 87 EO and 138 AO patients). Second, we explored the effect of NRN1 on brain activity during a working memory task (N-back task; 39 HS, 39 EO and 39 AO; matched by age, sex and estimated IQ). Different haplotypes encompassing the same three Single Nucleotide Polymorphisms(SNPs, rs3763180–rs10484320–rs4960155) were associated with EO in the two samples (GCT, TCC and GTT). Besides, the GTT haplotype was associated with worse N-back task performance in EO and was linked to an inefficient dorsolateral prefrontal cortex activity in subjects with EO compared to HS. Our results show convergent evidence on the NRN1 association with EO both from genetic and neuroimaging approaches, highlighting the role of neurotrophins in the pathophysiology of SZ.

Scoliosis and skeletal muscle mass are strongly associated with low back pain-related disability in humans: An evolutionary anthropology point of view.

To clarify the potential risk factors and etiology of low back pain (LBP)-related disability, including structural changes of the spine (spinal scoliosis) and body composition components in a population with a high prevalence of LBP. In this cross-sectional study, two self-reported validated questionnaires were used to collect back pain and disability data in an ethnically homogeneous family-based population sample (N =1078). The scoliosis angle of trunk rotation was measured by a scoliometer on three spinal levels while the patient was bent forward. Body composition parameters, including relative to weight (WT), fat, relative skeletal muscle mass (SMM/WT), and total body water were determined by bioelectrical impedance analysis. Statistical analysis was conducted, accounting for the familial composition of the sample. The mixed multiple regression analyses with several LBP-related phenotypes as dependent variables consistently showed significant independent associations with scoliosis and SMM/WT, irrespective of other covariates. The odds ratios (OR)/95% CI for scoliosis ranged between 1.40 (1.19-1.64) and 1.51 (1.27-1.80), and from 0.61(0.51-0.72), to 0.71(0.58-0.87) for SMM/WT, depending on the LBP phenotype. The genetic components of the respective correlations between the LBP-phenotypes and scoliosis or SMM/WT were negligible. The associations between LBP-related conditions and postured scoliosis and SMM/WT were consistent and significant and therefore may serve as markers in predicting the development of LBP-related disability. We interpret the origin of these correlations as the evolutionary event due to the imperfect spine anatomy adaptation to a vertical posture resulting from a quick transition to bipedalism from a quadrupedal ancestor.

Research Review: A guide to computing and implementing polygenic scores in developmental research.

The increasing availability of genotype data in longitudinal population- and family-based samples provides opportunities for using polygenic scores (PGS) to study developmental questions in child and adolescent psychology and psychiatry. Here, we aim to provide a comprehensive overview of how PGS can be generated and implemented in developmental psycho(patho)logy, with a focus on longitudinal designs. As such, the paper is organized into three parts: First, we provide a formal definition of polygenic scores and related concepts, focusing on assumptions and limitations. Second, we give a general overview of the methods used to compute polygenic scores, ranging from the classic approach to more advanced methods. We include recommendations and reference resources available to researchers aiming to conduct PGS analyses. Finally, we focus on the practical applications of PGS in the analysis of longitudinal data. We describe how PGS have been used to research developmental outcomes, and how they can be applied to longitudinal data to address developmental questions.

Stress-related genetic components in attention-deficit/hyperactivity disorder (ADHD): Effects of the SERPINA6 and SERPINA1 genetic markers in a family-based brazilian sample

SERPINA6 and SERPINA1 were recently identified as the main genes associated with plasma cortisol concentration in humans. Although dysregulation in the Hypothalamus–Pituitary-Adrenal (HPA) axis has been observed in Attention Deficit/Hyperactivity Disorder (ADHD), the molecular mechanisms underlying this relationship are still unclear. Evaluation of the SERPINA6/SERPINA1 gene cluster in ADHD may provide relevant information to uncover them. We tested the association between the SERPINA6/SERPINA1 locus, including 95 single nucleotide polymorphisms (SNPs), and ADHD, using data from a Brazilian clinical sample of 259 ADHD probands and their parents. The single SNP association was tested using binary logistic regression, and we performed Classification and Regression Tree (CART) analysis to evaluate genotype combinations' effects on ADHD susceptibility. We assessed SNPs’ regulatory effects through the Genotype-Tissue Expression (GTEx) v8 tool, and performed a complementary look-up analysis in the largest ADHD GWAS to date. There was a suggestive association between ADHD and eight variants located in the SERPINA6 region and one in the intergenic region between SERPINA6 and SERPINA1 after correction for multiple tests (p < 0.032). CART analysis showed that the combined effects of genotype GG in rs2144833 and CC in rs10129500 were associated with ADHD (OR = 1.78; CI95% = 1.24–2.55). The GTEx assigned the SNPs as eQTLs for genes in different tissues, including SERPINA6, and the look-up analysis revealed two SNPs associated with ADHD. These results suggest a shared genetic component between cortisol levels and ADHD. HPA dysregulation/altered stress response in ADHD might be mediated by upregulation of corticosteroid binding globulin (CBG, encoded by SERPINA6) expression.

Circulating Levels of Visceral Adipose Tissue-Derived Serine Protease Inhibitor (Vaspin) Appear as a Marker of Musculoskeletal Pain Disability.

Musculoskeletal pain (MSP), specifically low back pain (LBP), is often associated with several adipose tissue-derived cytokines (adipokines) and body composition, but their correlations with the LBP-related disability/severity phenotypes remain poorly understood. In this cross-sectional study, two self-reported validated questionnaires were used to collect back pain and disability data in an ethnically homogeneous family-based population sample (N = 1078). Plasma levels of relatively new adipokines, vaspin and adipsin, were detected by ELISA. Body composition parameters, including fat, skeletal muscle mass, extracellular water (ECW), and others were assessed through bioelectrical impedance analysis (BIA) technology. Statistical analysis was conducted, accounting for the familial composition of the sample. The multiple regression analyses with four LBP-related phenotypes as dependent variables consistently showed, for the first time, the significant associations with vaspin levels, regardless of other covariates. The odds ratios (OR)/SD ranged between 1.24 (95%CI = 1.03–1.50) and 1.33 (95%CI = 1.07–1.64), depending on the LBP phenotype. Among the tested body composition covariates, only ECW levels displayed consistent and highly significant associations with all tested LBP phenotypes (OR from 1.43, 95%CI = 1.14–1.79 to 1.68, 95%CI = 1.26–2.24). The results clearly suggest that circulating concentrations of vaspin and ECW levels could serve as biomarkers of MSP/LBP severity and complications.

Longitudinal Associations of Childhood Internalizing Psychopathology With Substance Misuse: A Register-Based Twin and Sibling Study

The pathways from internalizing psychopathology to substance misuse remain largely unclear. We estimated associations between childhood internalizing problems and subsequent substance misuse in 2 family-based samples. We also investigated sex differences and the role of externalizing comorbidity. We studied associations of childhood internalizing psychopathology with register-based substance misuse after age 13 years. Sample 1 included all individuals born in Sweden from 1984 to 2000 (N= 1,768,516). Depressive and anxiety disorders were included as register-based International Classification of Diseases Ninth Revision (ICD-9) or Tenth Revision (ICD-10) diagnoses before age 13. Sample 2 was a subsample within the population sample, the Child and Adolescent Twin Study in Sweden (CATSS) twin cohort (n= 12,408; born 1992-1998), with mood and anxiety problems assessed at age 9/12 by parents. In both samples, substance misuse was defined as an ICD-9/10 alcohol/drug use disorder or an alcohol/drug-related criminal conviction until December 2013. To account for familial effects, stratified analyses were conducted within siblings and twin pairs. In the population sample, both depressive (hazard ratio [HR]= 2.75, 95% CI= 2.36-3.20) and anxiety disorders (HR= 1.52, 95% CI= 1.35-1.73) were associated with substance misuse. Childhood mood problems (HR= 2.28, 95% CI= 1.69-3.08) were associated with substance misuse in the CATSS sample. The associations were partially explained by familial factors, and comorbid externalizing disorders explained the associations in men but not in women. Childhood mood problems were associated with substance misuse, but familial factors shared by siblings partially explained the associations. The relationship of anxiety with substance misuse was complex and depended on measurement and the type of anxiety disorder. Internalizing problems may be especially important for substance misuse risk in women.

Association study between vitiligo and autoimmune-related genes CYP27B1, REL, TNFAIP3, IL2 and IL21.

The aetiology of vitiligo has not been fully elucidated, and several hypotheses have been investigated; among them, the most explored assumes an autoimmune basis for the disease. Supporting this hypothesis is the frequent co-occurrence of autoimmune diseases with vitiligo. In addition, various genetic loci associated with vitiligo harbour key immune response genes. Our general hypothesis is that autoimmunity-associated genes participate in the control of vitiligo susceptibility. To investigate this hypothesis, we tested for association between vitiligo and genes CYP27B1, REL, TNFAIP3 and IL2/IL21, all previously related to autoimmune diseases associated with vitiligo. The study was performed using two independent population samples: a family-based discovery set (211 trios) and a replication set (131 cases/119 controls). Statistically significant association with vitiligo was detected between markers of the REL and IL2 gene in the family-based sample. Both association signals were concentrated among patients displaying autoimmune comorbidity and non-segmental vitiligo. Evidence for validation was detected for IL2 marker. Our findings suggest REL and IL2 as new vitiligo susceptibility genes and reinforce the hypothesis of a shared genetic mechanism controlling vitiligo and other autoimmune diseases.

Fast Algorithms for Conducting Large-Scale GWAS of Age-at-Onset Traits Using Cox Mixed-Effects Models.

Age-at-onset is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of age-at-onset traits can provide more insights into genetic effects on disease progression and transitions between stages. Moreover, proportional hazards (or Cox) regression models can achieve higher statistical power in a cohort study than a case-control trait using logistic regression. Although mixed-effects models are widely used in GWAS to correct for sample dependence, application of Cox mixed-effects models (CMEMs) to large-scale GWAS is so far hindered by intractable computational cost. In this work, we propose COXMEG, an efficient R package for conducting GWAS of age-at-onset traits using CMEMs. COXMEG introduces fast estimation algorithms for general sparse relatedness matrices including, but not limited to, block-diagonal pedigree-based matrices. COXMEG also introduces a fast and powerful score test for dense relatedness matrices, accounting for both population stratification and family structure. In addition, COXMEG generalizes existing algorithms to support positive semidefinite relatedness matrices, which are common in twin and family studies. Our simulation studies suggest that COXMEG, depending on the structure of the relatedness matrix, is orders of magnitude computationally more efficient than coxme and coxph with frailty for GWAS. We found that using sparse approximation of relatedness matrices yielded highly comparable results in controlling false-positive rate and retaining statistical power for an ethnically homogeneous family-based sample. By applying COXMEG to a study of Alzheimer's disease (AD) with a Late-Onset Alzheimer's Disease Family Study from the National Institute on Aging sample comprising 3456 non-Hispanic whites and 287 African Americans, we identified the APOE ε4 variant with strong statistical power (P = 1e-101), far more significant than that reported in a previous study using a transformed variable and a marginal Cox model. Furthermore, we identified novel SNP rs36051450 (P = 2e-9) near GRAMD1B, the minor allele of which significantly reduced the hazards of AD in both genders. These results demonstrated that COXMEG greatly facilitates the application of CMEMs in GWAS of age-at-onset traits.

Genome-wide association study of word reading: Overlap with risk genes for neurodevelopmental disorders.

Reading disabilities (RD) are the most common neurocognitive disorder, affecting 5% to 17% of children in North America. These children often have comorbid neurodevelopmental/psychiatric disorders, such as attention deficit/hyperactivity disorder (ADHD). The genetics of RD and their overlap with other disorders is incompletely understood. To contribute to this, we performed a genome-wide association study (GWAS) for word reading. Then, using summary statistics from neurodevelopmental/psychiatric disorders, we computed polygenic risk scores (PRS) and used them to predict reading ability in our samples. This enabled us to test the shared aetiology between RD and other disorders. The GWAS consisted of 5.3 million single nucleotide polymorphisms (SNPs) and two samples; a family-based sample recruited for reading difficulties in Toronto (n = 624) and a population-based sample recruited in Philadelphia [Philadelphia Neurodevelopmental Cohort (PNC)] (n = 4430). The Toronto sample SNP-based analysis identified suggestive SNPs (P ~ 5 × 10-7 ) in the ARHGAP23 gene, which is implicated in neuronal migration/axon pathfinding. The PNC gene-based analysis identified significant associations (P < 2.72 × 10-6 ) for LINC00935 and CCNT1, located in the region of the KANSL2/CCNT1/LINC00935/SNORA2B/SNORA34/MIR4701/ADCY6 genes on chromosome 12q, with near significant SNP-based analysis. PRS identified significant overlap between word reading and intelligence (R2 = 0.18, P = 7.25 × 10-181 ), word reading and educational attainment (R2 = 0.07, P = 4.91 × 10-48 ) and word reading and ADHD (R2 = 0.02, P = 8.70 × 10-6 ; threshold for significance = 7.14 × 10-3 ). Overlap was also found between RD and autism spectrum disorder (ASD) as top-ranked genes were previously implicated in autism by rare and copy number variant analyses. These findings support shared risk between word reading, cognitive measures, educational outcomes and neurodevelopmental disorders, including ASD.

KTN1 variants and risk for attention deficit hyperactivity disorder.

Individuals with attention deficit hyperactivity disorder (ADHD) show gray matter volume (GMV) reduction in the putamen. KTN1 variants may regulate kinectin 1 expression in the putamen and influence putamen structure and function. We aim to test the hypothesis that the KTN1 variants may represent a genetic risk factor of ADHD. Two independent family-based Caucasian samples were analyzed, including 922 parent-child trios (a total of 2,757 subjects with 924 ADHD children) and 735 parent-child trios (a total of 1,383 subjects with 613 ADHD children). The association between ADHD and a total of 143 KTN1 SNPs was analyzed in the first sample, and the nominally-significant (p < .05) risk SNPs were classified into independent haplotype blocks. All SNPs, including imputed SNPs within these blocks, and haplotypes across each block, were explored for replication of associations in both samples. The potential biological functions of all risk SNPs were predicted using a series of bioinformatics analyses, their regulatory effects on the putamen volumes were tested, and the KTN1 mRNA expression was examined in three independent human putamen tissue samples. We found that fifteen SNPs were nominally associated with ADHD (p < .05) in the first sample, and three of them remained significant even after correction for multiple testing (1.3 × 10-10 ≤ p ≤ 1.2 × 10-4 ; α = 2.5 × 10-3 ). These 15 risk SNPs were located in five haplotype blocks, and 13 SNPs within four of these blocks were associated with ADHD in the second sample. Six haplotypes within these blocks were also significantly (1.2 × 10-7 ≤ p ≤ .009) associated with ADHD in these samples. These risk variants were located in disease-related transposons and/or transcription-related functional regions. Major alleles of these risk variants significantly increased putamen volumes. Finally, KTN1 mRNA was significantly expressed in putamen across three independent cohorts. We concluded that the KTN1 variants were significantly associated with ADHD. KTN1 may play a functional role in the development of ADHD.

Significant, replicable, and functional associations between KTN1 variants and alcohol and drug codependence.

The gray matter volume (GMV) of the putamen has been reported to be regulated by kinectin 1 gene (KTN1). As a hub of the dopaminergic circuit, the putamen is widely implicated in the etiological processes of substance use disorders (SUD). Here, we aimed to identify robust and reliable associations between KTN1 SNPs and SUD across multiple samples. We examined the associations between SUD and KTN1 SNPs in four independent population-based or family-based samples (n = 10,209). The potential regulatory effects of the risk alleles on the putamen GMVs, the effects of alcohol, nicotine, marijuana and cocaine on KTN1 mRNA expression, and the relationship between KTN1 mRNA expression and SUD were explored. We found that a total of 23 SNPs were associated with SUD across at least two independent samples (1.4 × 10-4 ≤ p ≤ 0.049), including one SNP (rs12895072) across three samples (8.8 × 10-3 ≤ p ≤ 0.049). Four other SNPs were significantly or suggestively associated with SUD only in European-Australians (4.8 × 10-4 ≤ p ≤ 0.058). All of the SUD-risk alleles of these 27 SNPs increased (β > 0) the putamen GMVs and represented major alleles (f > 0.5) in Europeans. Twenty-two SNPs were potentially biologically functional. Alcohol, nicotine and cocaine significantly affected the KTN1 mRNA expression, and the KTN1 mRNA was differentially expressed between nicotine or cocaine dependent and control subjects. We concluded that there was a replicable and robust relationship among the KTN1 variants, KTN1 mRNA expression, putamen GMVs, molecular effects of substances, and SUD, suggesting that some risk KTN1 alleles might increase kinectin 1 expression in the putamen, altering putamen structures and functions, and leading to SUD.

Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family-based samples.

Numerous methods for estimating heritability have been proposed; however, unlike quantitative phenotypes, heritability estimation for dichotomous phenotypes is computationally and statistically complex, and the use of heritability is infrequent. In this study, we developed a statistical method to estimate heritability of dichotomous phenotypes using a liability threshold model in the context of ascertained family-based samples. This model assumes that dichotomous phenotypes are determined by unobserved latent variables that are normally distributed and can be applied to general pedigree data. The proposed methods were applied to simulated data and Korean type-2 diabetes family-based samples, and the accuracy of the estimates provided by the experimental methods was compared with that of the established methods.

MetaFARVAT: An Efficient Tool for Meta-Analysis of Family-Based, Case-Control, and Population-Based Rare Variant Association Studies.

Family-based designs have been shown to be powerful in detecting the significant rare variants associated with human diseases. However, very few significant results have been found owing to relatively small sample sizes and the fact that statistical analyses often suffer from high false-negative error rates. These limitations can be avoided by combining results from multiple studies via meta-analysis. However, statistical methods for meta-analysis with rare variants are limited for family-based samples. In this report, we propose a tool for the meta-analysis of family-based rare variant associations, metaFARVAT. metaFARVAT is based on a quasi-likelihood score for each variant. These scores are combined to generate burden test, variable-threshold test, sequence kernel association test (SKAT), and optimal SKAT statistics. The proposed method tests homogeneous and heterogeneous effects of variants among different studies and can be applied to both quantitative and dichotomous phenotypes. Simulation results demonstrated the robustness and efficiency of the proposed method in different scenarios. By applying metaFARVAT to data from a family-based study and a case-control study, we identified a few promising candidate genes, including DLEC1, which is associated with chronic obstructive pulmonary disease.

KCNJ6 variants modulate reward-related brain processes and impact executive functions in attention-deficit/hyperactivity disorder.

KCNJ6, encoding a potassium channel subunit, regulates the excitability of dopaminergic neurons and is expressed in attention-deficit/hyperactivity disorder (ADHD)-relevant brain regions. As a potential ADHD risk gene, KCNJ6, therefore, may contribute to the endophenotypic variation of the disorder. The impact of two SNPs, rs7275707 and rs6517442, both located in the transcriptional control region of KCNJ6, on reporter gene expression was explored in cultured cells. The KCNJ6 variants were then tested for association with ADHD and personality traits in a family-based sample (165 affected children) and an adult case-control sample (450 patients, 426 controls). Furthermore, the genotypic influence on performance in an n-back task and a cued continuous performance test (cCPT) was investigated by electroencephalography recordings. Finally, rs6517442 function was assessed by a reward anticipation paradigm using functional magnetic resonance imaging. Different haplotypes of rs7275707 and rs6517442 significantly influenced KCNJ6 gene expression proving their functional relevance on the molecular level. In the family-based children sample rs7275707 was associated with ADHD (p = .038). Moreover, rs7275707 showed association with the personality trait of Reward Dependence (p = .031). In the ADHD group, both rs7275707 and rs6517442 influenced the Go-centroid location in the cCPT and the N200 amplitude in the n-back task. Furthermore, ventral striatal activation was impacted by rs6517442 during reward anticipation. Our data indicate that functional variants of KCNJ6 influence brain activity during reward-related and executive processes supporting the view of a differential, age-dependent modulatory impact of dopamine-related brain processes in ADHD risk.

ADGRL3 (LPHN3) variants predict substance use disorder

Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.