The SNP-set based association study identifies ITGA1 as a susceptibility gene of attention-deficit/hyperactivity disorder in Han Chinese

Racial differences in the effect of APOE-ε4 genotypes on trail making test B in Alzheimer's disease: A longitudinal study

OBJECTIVES

The trail making test part B (TMT-B) evaluates executive functions, memory, and sensorimotor functions. No previous study was found to examine the longitudinal effect of APOE-ε4 genotypes on the TMT-B scores in Alzheimer's disease (AD) across racial groups.

METHODS

This study used the data from Alzheimer's Disease Neuroimaging Initiative (ADNI): 382 participants with AD, 503 with cognitive normal (CN), 1293 with mild cognitive impairment (MCI) at baseline and follow-up of four years. The multivariable linear mixed model was used to investigate the effect of APOE-ε4 genotypes on changes in TMT-B scores.

RESULTS

Compared with Whites, African Americans (AA) and Hispanics had higher TMT-B scores (poor cognitive function). Furthermore, Whites subjects with 1 or 2 APOE-ε4 alleles had significantly higher TMT-B scores compared with individuals without APOE-ε4 allele at baseline and four follow-up visits; however, no differences in TMT-B were found between APOE-ε4 alleles in the Hispanic and AA groups. No APOE-ε4 by visit interactions was found for 3 racial groups. Stratified by AD diagnosis, the APOE-ε4 allele was associated with TMT-B scores only in the MCI group, while there were significant interactions for visit by education, APOE-ε4 allele, and the Mini Mental State Examination (MMSE) score in the MCI group. In addition, TMT-B was significantly correlated with the MMSE, AD Assessment Scale-cognitive subscale 13 (ADAS13), tTau, pTau, Aβ42, and hippocampus.

CONCLUSIONS

APOE-ɛ4 allele is associated with TMT-B scores in Whites subjects, but not in the Hispanic and AA groups. APOE-ε4 showed interaction with visit in the MCI group.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

BACKGROUND

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

METHOD

A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

RESULTS

We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

CONCLUSION

The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the risk ADHD-associated variants and genes with significant P-values, they may neglect the combined effect of multiple variants with insignificant P-values. Here, we proposed a convolutional neural network (CNN) to classify 1033 individuals diagnosed with ADHD from 950 healthy controls according to their genomic data. The model takes the single nucleotide polymorphism (SNP) loci of P-values $\le{1\times 10^{-3}}$, i.e. 764 loci, as inputs, and achieved an accuracy of 0.9018, AUC of 0.9570, sensitivity of 0.8980 and specificity of 0.9055. By incorporating the saliency analysis for the deep learning network, a total of 96 candidate genes were found, of which 14 genes have been reported in previous ADHD-related studies. Furthermore, joint Gene Ontology enrichment and expression Quantitative Trait Loci analysis identified a potential risk gene for ADHD, EPHA5 with a variant of rs4860671. Overall, our CNN deep learning model exhibited a high accuracy for ADHD classification and demonstrated that the deep learning model could capture variants' combining effect with insignificant P-value, while GWAS fails. To our best knowledge, our model is the first deep learning method for the classification of ADHD with SNPs data.

The Co-existence of ADHD With Autism in Saudi Children: An Analysis Using Next-Generation DNA Sequencing

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders. Several studies have confirmed the co-existence of other neuropsychiatric disorders with ADHD. Out of 106 individuals suspected to have ADHD, eight Saudi Arabian pediatric patients were diagnosed with ADHD using a dual assessment procedure based on highly significant scores from the international criteria for diagnosis; (full form DMS) DSM-5. Then, these patients were examined for the co-existence of autism and ADHD using different international diagnostic protocols. Four patients with combined ADHD and autism and four ADHD patients without autism were examined for the presence of genetic variants. Six variants (chr1:98165091, chr6:32029183, chr6:32035603, chr6:32064098, chr8:2909992, chr16:84213434) were identified in 75% of the patients with ADHD and autism, indicating that these genes may have a possible role in causing autism. Five variants (The chr2:116525960, chr15:68624396, chr15:91452595, chr15:92647645, and chr16:82673047) may increase to the severity of ADHD. This study recommends screening these eleven variants in ADHD cases and their relevant controls to confirm the prevalence in the Saudi population. It is recommended that future studies examine the 11 variants in detail.

Copy number variants in siblings of Mexican origin concordant for schizophrenia or bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) cause similar symptomatology. A correlation between these disorders has been found. We aimed to explore shared CNVs between SCZ and BD, in 35 sibpairs diagnosed with SCZ and 21 sibpairs diagnosed with BD. CNV calling was performed using data derived of Psycharray, by PennCNV. We did not find any shared CNVs between individuals diagnosed with BD and SCZ, neither with psychotic symptoms in individuals with BD. Nevertheless, we found a significant higher CNV burden in early-onset SCZ. This is one of the first's studies analyzing shared CNVs between SCZ and BD in Mexican population.

The Implicated Roles of Cell Adhesion Molecule 1 (CADM1) Gene and Altered Prefrontal Neuronal Activity in Attention-Deficit/Hyperactivity Disorder: A "Gene-Brain-Behavior Relationship"?

Background: Genes related to cell adhesion pathway have been implicated in the genetic architecture of attention-deficit/hyperactivity disorder (ADHD). Cell adhesion molecule 1, encoded by CADM1 gene, is a protein which facilitates cell adhesion, highly expressed in the human prefrontal lobe. This study aimed to evaluate the association of CADM1 genotype with ADHD, executive function, and regional brain functions.

Methods: The genotype data of 10-tag single nucleotide polymorphisms of CADM1 for 1,040 children and adolescents with ADHD and 963 controls were used for case–control association analyses. Stroop color–word interference test, Rey–Osterrieth complex figure test, and trail making test were conducted to assess “inhibition,” “working memory,” and “set-shifting,” respectively. A subsample (35 ADHD versus 56 controls) participated in the nested imaging genetic study. Resting-state functional magnetic resonance images were acquired, and the mean amplitude of low-frequency fluctuations (mALFF) were captured.

Results: Nominal significant genotypic effect of rs10891819 in “ADHD-alone” subgroup was detected (P = 0.008) with TT genotype as protective. The results did not survive multiple testing correction. No direct genetic effect was found for performance on executive function tasks. In the imaging genetic study for the “ADHD-whole” sample, rs10891819 genotype was significantly associated with altered mALFF in the right superior frontal gyrus (rSFG, peak t = 3.85, corrected P < 0.05). Specifically, the mALFFs in T-allele carriers were consistently higher than GG carriers in ADHD and control groups. Endophenotypic correlation analyses indicated a significant negative correlation between “word interference time” in Stroop (shorter “word interference time” indexing better inhibitory function) and mALFF in the rSFG (r = -0.29, P = 0.006). Finally, mediation analysis confirmed significant indirect effects from “rs10891819 genotype (T-allele carriers)” via “mALFF (rSFG)” to “inhibition (“word interference time”)” (Sobelz = -2.47; B = -2.61, 95% confidence interval -0.48 to -4.72; P = 0.009).

Conclusions: Our study offered preliminary evidence to implicate the roles of CADM1 in relation to prefrontal brain activities, inhibition function, and ADHD, indicating a potential “gene–brain–behavior” relationship of the CADM1 gene. Future studies with larger samples may specifically test these hypotheses generated by our exploratory findings.

[Genetics and epigenetics of attention deficit hyperactivity disorder]

Molecular genetic studies of attention deficit hyperactivity disorder (ADHD) have demonstrated the involvement of multiple genes in the etiology of ADHD. A polygenic hypothesis of the etiopathogenesis was formulated without clear knowledge of common mechanisms of ADHD development. Twin, family and adoption studies have established the heritability of 70-80% for ADHD. Association studies have shown the relationship between ADHD and genes of dopaminergic (DRD4, DRD5, SLC6A3), serotoninergic (HTR1B, 5-HTTLPR), glutamatergic (mGluR, NDRG2) systems, metabolic pathways (SLC2A3, SLC6A4, CDH13, CFOD1, GFOD1), membrane proteins (KChIP1, ITGA1, SNAP-25) as well as tumour-suppressor (NDRG2, NF1) and cytokine genes. The marked comorbidity of ADHD with other psychiatric disorders and shared genetic risk factors were determined. Studies of a role of copy number variations (CNVs) provided more promising evidence that suggested the possible involvement of retroelements as the unifying factors of disease etiopathogenesis. Transposons, which are sensitive to stress, may cause CNVs and are key regulators of brain development and functioning. The dysregulation of transposons is thought to be important in changes in tuning of gene regulatory pathways and epigenetic regulation of neurons in ADHD that may be a common principle underlying the heterogeneous nature of ADHD. Research on noncoding RNAs will help to confirm the hypothesis and develop diagnostic algorithms of examination of ADHD patients as an important step in the implementation of personalized medicine in psychiatry.

Recent developments in the genetics of attention-deficit hyperactivity disorder

Attention-deficit hyperactivity disorder (ADHD) is a developmental psychiatric disorder that affects children and adults. ADHD is one of the psychiatric disorders with the strongest genetic basis according to familial, twin, and single nucleotide polymorphisms (SNP)-based epidemiological studies. In this review, we provide an update of recent insights into the genetic basis of ADHD. We discuss recent progress from genome-wide association studies (GWAS) looking at common variants as well as rare copy number variations. New analysis of gene groups, so-called functional ontologies, provide some insight into the gene networks afflicted, pointing to the role of neurodevelopmentally expressed gene networks. Bioinformatic methods, such as functional enrichment analysis and protein-protein network analysis, are used to highlight biological processes of likely relevance to the etiology of ADHD. Additionally, copy number variations seem to map on important pathways implicated in synaptic signaling and neurodevelopment. While some candidate gene associations of, for example, neurotransmitter receptors and signaling, have been replicated, they do not seem to explain significant variance in recent GWAS. We discuss insights from recent case-control SNP-GWAS that have presented the first whole-genome significant SNP in ADHD.