Phenotypic and genetic analysis of cognitive performance in Major Depressive Disorder in the Generation Scotland:Scottish Family Health Study

Abstract Lower performances in cognitive ability in individuals with Major Depressive Disorder (MDD) have been observed on multiple occasions. Understanding cognitive performance in MDD could provide a wider insight in the aetiology of MDD as a whole. Using a large, well characterised cohort (N = 7012), we tested for: differences in cognitive performance by MDD status and a gene (single SNP or polygenic score) by MDD interaction effect on cognitive performance. Linear regression was used to assess the association between cognitive performance and MDD status in a case-control, single-episode–recurrent MDD and control-recurrent MDD study design. Test scores on verbal declarative memory, executive functioning, vocabulary, and processing speed were examined. Cognitive performance measures showing a significant difference between groups were subsequently analysed for genetic associations. Those with recurrent MDD have lower processing speed versus controls and single-episode MDD (β =  −2.44, p = 3.6 × 10−04; β =  -2.86, p = 1.8 × 10−03, respectively). There were significantly higher vocabulary scores in MDD cases versus controls (β = 0.79, p = 2.0 × 10−06), and for recurrent MDD versus controls (β = 0.95, p  = 5.8 × 10−05). Observed differences could not be linked to significant single-locus associations. Polygenic scores created from a processing speed meta-analysis GWAS explained 1% of variation in processing speed performance in the single-episode versus recurrent MDD study (p = 1.7 × 10−03) and 0.5% of variation in the control versus recurrent MDD study (p = 1.6 × 10−10). Individuals with recurrent MDD showed lower processing speed and executive function while showing higher vocabulary performance. Within MDD, persons with recurrent episodes show lower processing speed and executive function scores relative to individuals experiencing a single episode

Genome­-wide association study of alcohol consumption and genetic overlap with other health-­related traits in UK Biobank (<i>N </i>=112,117)

Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well-known genetic variants in alcohol metabolizing genes, for example, ALDH2 and ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112 117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 14 loci. These include single-nucleotide polymorphisms (SNPs) in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and two loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, CADM2 and FAM69C. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (DRD2, PDE4B). GCTA analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (se=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation (rG) between male and female alcohol consumption was 0.90 (s.e.=0.09, P-value=7.16 × 10(-23)). Using LD score regression, genetic overlap was found between alcohol consumption and years of schooling (rG=0.18, s.e.=0.03), high-density lipoprotein cholesterol (rG=0.28, s.e.=0.05), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19, s.e.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption

Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression

Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects

A novel Alzheimer disease locus located near the gene encoding tau protein.

APOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ɛ4+ (10 352 cases and 9207 controls) and APOE ɛ4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ɛ4 status. Suggestive associations (P<1 × 10(-4)) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ɛ4+: 1250 cases and 536 controls; APOE ɛ4-: 718 cases and 1699 controls). Among APOE ɛ4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10(-9)). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ɛ4+ subjects (CR1 and CLU) or APOE ɛ4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10(-7)) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P ⩽ 1.3 × 10(-8)), frontal cortex (P ⩽ 1.3 × 10(-9)) and temporal cortex (P⩽1.2 × 10(-11)). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10(-6)) and temporal cortex (P=2.6 × 10(-6)). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ɛ4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted

Genetic contributions to variation in general cognitive function:a meta-analysis of genome-wide association studies in the CHARGE consortium (<i>N</i>=53 949)

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer’s disease: TOMM40, APOE, ABCG1 and MEF2C

Interactions between PPAR-α and inflammation-related cytokine genes on the development of Alzheimer’s disease, observed by the Epistasis Project

OBJECTIVE: Neuroinflammation contributes to the pathogenesis of sporadic Alzheimer's disease (AD). Variations in genes relevant to inflammation may be candidate genes for AD risk. Whole-genome association studies have identified relevant new and known genes. Their combined effects do not explain 100% of the risk, genetic interactions may contribute. We investigated whether genes involved in inflammation, i.e. PPAR-α, interleukins (IL) IL- 1α, IL-1β, IL-6, and IL-10 may interact to increase AD risk. METHODS: The Epistasis Project identifies interactions that affect the risk of AD. Genotyping of single nucleotide polymorphisms (SNPs) in PPARA, IL1A, IL1B, IL6 and IL10 was performed. Possible associations were analyzed by fitting logistic regression models with AD as outcome, controlling for centre, age, sex and presence of apolipoprotein ε4 allele (APOEε4). Adjusted synergy factors were derived from interaction terms (p<0.05 two-sided). RESULTS: We observed four significant interactions between different SNPs in PPARA and in interleukins IL1A, IL1B, IL10 that may affect AD risk. There were no significant interactions between PPARA and IL6. CONCLUSIONS: In addition to an association of the PPARA L162V polymorphism with the AD risk, we observed four significant interactions between SNPs in PPARA and SNPs in IL1A, IL1B and IL10 affecting AD risk. We prove that gene-gene interactions explain part of the heritability of AD and are to be considered when assessing the genetic risk. Necessary replications will require between 1450 and 2950 of both cases and controls, depending on the prevalence of the SNP, to have 80% power to detect the observed synergy factors