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Fulltext The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Coleman JRI, Gaspar HA, Bryois J, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Breen G

Biol Psychiatry, 2020 Jul 15;88(2):169-184.
PMID: 31926635 DOI: 10.1016/j.biopsych.2019.10.015

BACKGROUND: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.
METHODS: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).
RESULTS: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.
CONCLUSIONS: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Genome-wide association analyses identify new susceptibility loci for oral cavity and pharyngeal cancer

Lesseur C, Diergaarde B, Olshan AF, Wünsch-Filho V, Ness AR, Liu G, et al.

Nat Genet, 2016 Dec;48(12):1544-1550.
PMID: 27749845 DOI: 10.1038/ng.3685

We conducted a genome-wide association study of oral cavity and pharyngeal cancer in 6,034 cases and 6,585 controls from Europe, North America and South America. We detected eight significantly associated loci (P < 5 × 10-8), seven of which are new for these cancer sites. Oral and pharyngeal cancers combined were associated with loci at 6p21.32 (rs3828805, HLA-DQB1), 10q26.13 (rs201982221, LHPP) and 11p15.4 (rs1453414, OR52N2-TRIM5). Oral cancer was associated with two new regions, 2p23.3 (rs6547741, GPN1) and 9q34.12 (rs928674, LAMC3), and with known cancer-related loci-9p21.3 (rs8181047, CDKN2B-AS1) and 5p15.33 (rs10462706, CLPTM1L). Oropharyngeal cancer associations were limited to the human leukocyte antigen (HLA) region, and classical HLA allele imputation showed a protective association with the class II haplotype HLA-DRB1*1301-HLA-DQA1*0103-HLA-DQB1*0603 (odds ratio (OR) = 0.59, P = 2.7 × 10-9). Stratified analyses on a subgroup of oropharyngeal cases with information available on human papillomavirus (HPV) status indicated that this association was considerably stronger in HPV-positive (OR = 0.23, P = 1.6 × 10-6) than in HPV-negative (OR = 0.75, P = 0.16) cancers.

Matched MeSH terms: Genome-Wide Association Study*
Fulltext Identification of common genetic risk variants for autism spectrum disorder

Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al.

Nat Genet, 2019 03;51(3):431-444.
PMID: 30804558 DOI: 10.1038/s41588-019-0344-8

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

Matched MeSH terms: Genome-Wide Association Study/methods
Genetic Association of Major Depression With Atypical Features and Obesity-Related Immunometabolic Dysregulations

Milaneschi Y, Lamers F, Peyrot WJ, Baune BT, Breen G, Dehghan A, et al.

JAMA Psychiatry, 2017 12 01;74(12):1214-1225.
PMID: 29049554 DOI: 10.1001/jamapsychiatry.2017.3016

Importance: The association between major depressive disorder (MDD) and obesity may stem from shared immunometabolic mechanisms particularly evident in MDD with atypical features, characterized by increased appetite and/or weight (A/W) during an active episode.
Objective: To determine whether subgroups of patients with MDD stratified according to the A/W criterion had a different degree of genetic overlap with obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin).
Design, Setting, and Patients: This multicenter study assembled genome-wide genotypic and phenotypic measures from 14 data sets of the Psychiatric Genomics Consortium. Data sets were drawn from case-control, cohort, and population-based studies, including 26 628 participants with established psychiatric diagnoses and genome-wide genotype data. Data on BMI were available for 15 237 participants. Data were retrieved and analyzed from September 28, 2015, through May 20, 2017.
Main Outcomes and Measures: Lifetime DSM-IV MDD was diagnosed using structured diagnostic instruments. Patients with MDD were stratified into subgroups according to change in the DSM-IV A/W symptoms as decreased or increased.
Results: Data included 11 837 participants with MDD and 14 791 control individuals, for a total of 26 628 participants (59.1% female and 40.9% male). Among participants with MDD, 5347 (45.2%) were classified in the decreased A/W and 1871 (15.8%) in the increased A/W subgroups. Common genetic variants explained approximately 10% of the heritability in the 2 subgroups. The increased A/W subgroup showed a strong and positive genetic correlation (SE) with BMI (0.53 [0.15]; P = 6.3 × 10-4), whereas the decreased A/W subgroup showed an inverse correlation (-0.28 [0.14]; P = .06). Furthermore, the decreased A/W subgroup had a higher polygenic risk for increased BMI (odds ratio [OR], 1.18; 95% CI, 1.12-1.25; P = 1.6 × 10-10) and levels of CRP (OR, 1.08; 95% CI, 1.02-1.13; P = 7.3 × 10-3) and leptin (OR, 1.09; 95% CI, 1.06-1.12; P = 1.7 × 10-3).
Conclusions and Relevance: The phenotypic associations between atypical depressive symptoms and obesity-related traits may arise from shared pathophysiologic mechanisms in patients with MDD. Development of treatments effectively targeting immunometabolic dysregulations may benefit patients with depression and obesity, both syndromes with important disability.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Genetic determinants of telomere length and risk of pancreatic cancer: A PANDoRA study

Campa D, Matarazzi M, Greenhalf W, Bijlsma M, Saum KU, Pasquali C, et al.

Int J Cancer, 2019 03 15;144(6):1275-1283.
PMID: 30325019 DOI: 10.1002/ijc.31928

Telomere deregulation is a hallmark of cancer. Telomere length measured in lymphocytes (LTL) has been shown to be a risk marker for several cancers. For pancreatic ductal adenocarcinoma (PDAC) consensus is lacking whether risk is associated with long or short telomeres. Mendelian randomization approaches have shown that a score built from SNPs associated with LTL could be used as a robust risk marker. We explored this approach in a large scale study within the PANcreatic Disease ReseArch (PANDoRA) consortium. We analyzed 10 SNPs (ZNF676-rs409627, TERT-rs2736100, CTC1-rs3027234, DHX35-rs6028466, PXK-rs6772228, NAF1-rs7675998, ZNF208-rs8105767, OBFC1-rs9420907, ACYP2-rs11125529 and TERC-rs10936599) alone and combined in a LTL genetic score ("teloscore", which explains 2.2% of the telomere variability) in relation to PDAC risk in 2,374 cases and 4,326 controls. We identified several associations with PDAC risk, among which the strongest were with the TERT-rs2736100 SNP (OR = 1.54; 95%CI 1.35-1.76; p = 1.54 × 10-10 ) and a novel one with the NAF1-rs7675998 SNP (OR = 0.80; 95%CI 0.73-0.88; p = 1.87 × 10-6 , ptrend = 3.27 × 10-7 ). The association of short LTL, measured by the teloscore, with PDAC risk reached genome-wide significance (p = 2.98 × 10-9 for highest vs. lowest quintile; p = 1.82 × 10-10 as a continuous variable). In conclusion, we present a novel genome-wide candidate SNP for PDAC risk (TERT-rs2736100), a completely new signal (NAF1-rs7675998) approaching genome-wide significance and we report a strong association between the teloscore and risk of pancreatic cancer, suggesting that telomeres are a potential risk factor for pancreatic cancer.

Matched MeSH terms: Genome-Wide Association Study
Fulltext DNA methylation and exposure to ambient air pollution in two prospective cohorts

Plusquin M, Guida F, Polidoro S, Vermeulen R, Raaschou-Nielsen O, Campanella G, et al.

Environ Int, 2017 11;108:127-136.
PMID: 28843141 DOI: 10.1016/j.envint.2017.08.006

Long-term exposure to air pollution has been associated with several adverse health effects including cardiovascular, respiratory diseases and cancers. However, underlying molecular alterations remain to be further investigated. The aim of this study is to investigate the effects of long-term exposure to air pollutants on (a) average DNA methylation at functional regions and, (b) individual differentially methylated CpG sites. An assumption is that omic measurements, including the methylome, are more sensitive to low doses than hard health outcomes. This study included blood-derived DNA methylation (Illumina-HM450 methylation) for 454 Italian and 159 Dutch participants from the European Prospective Investigation into Cancer and Nutrition (EPIC). Long-term air pollution exposure levels, including NO2, NOx, PM2.5, PMcoarse, PM10, PM2.5 absorbance (soot) were estimated using models developed within the ESCAPE project, and back-extrapolated to the time of sampling when possible. We meta-analysed the associations between the air pollutants and global DNA methylation, methylation in functional regions and epigenome-wide methylation. CpG sites found differentially methylated with air pollution were further investigated for functional interpretation in an independent population (EnviroGenoMarkers project), where (N=613) participants had both methylation and gene expression data available. Exposure to NO2 was associated with a significant global somatic hypomethylation (p-value=0.014). Hypomethylation of CpG island's shores and shelves and gene bodies was significantly associated with higher exposures to NO2 and NOx. Meta-analysing the epigenome-wide findings of the 2 cohorts did not show genome-wide significant associations at single CpG site level. However, several significant CpG were found if the analyses were separated by countries. By regressing gene expression levels against methylation levels of the exposure-related CpG sites, we identified several significant CpG-transcript pairs and highlighted 5 enriched pathways for NO2 and 9 for NOx mainly related to the immune system and its regulation. Our findings support results on global hypomethylation associated with air pollution, and suggest that the shores and shelves of CpG islands and gene bodies are mostly affected by higher exposure to NO2 and NOx. Functional differences in the immune system were suggested by transcriptome analyses.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Epigenome-wide association study of adiposity and future risk of obesity-related diseases

Campanella G, Gunter MJ, Polidoro S, Krogh V, Palli D, Panico S, et al.

Int J Obes (Lond), 2018 Dec;42(12):2022-2035.
PMID: 29713043 DOI: 10.1038/s41366-018-0064-7

BACKGROUND: Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction.
METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.
RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P

Matched MeSH terms: Genome-Wide Association Study
Fulltext Enterobacter asburiae strain L1: complete genome and whole genome optical mapping analysis of a quorum sensing bacterium

Lau YY, Yin WF, Chan KG

Sensors (Basel), 2014;14(8):13913-24.
PMID: 25196111 DOI: 10.3390/s140813913

Enterobacter asburiae L1 is a quorum sensing bacterium isolated from lettuce leaves. In this study, for the first time, the complete genome of E. asburiae L1 was sequenced using the single molecule real time sequencer (PacBio RSII) and the whole genome sequence was verified by using optical genome mapping (OpGen) technology. In our previous study, E. asburiae L1 has been reported to produce AHLs, suggesting the possibility of virulence factor regulation which is quorum sensing dependent. This evoked our interest to study the genome of this bacterium and here we present the complete genome of E. asburiae L1, which carries the virulence factor gene virK, the N-acyl homoserine lactone-based QS transcriptional regulator gene luxR and the N-acyl homoserine lactone synthase gene which we firstly named easI. The availability of the whole genome sequence of E. asburiae L1 will pave the way for the study of the QS-mediated gene expression in this bacterium. Hence, the importance and functions of these signaling molecules can be further studied in the hope of elucidating the mechanisms of QS-regulation in E. asburiae. To the best of our knowledge, this is the first documentation of both a complete genome sequence and the establishment of the molecular basis of QS properties of E. asburiae.

Matched MeSH terms: Genome-Wide Association Study/methods
Fulltext Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression

Darabi H, McCue K, Beesley J, Michailidou K, Nord S, Kar S, et al.

Am J Hum Genet, 2015 Jul 02;97(1):22-34.
PMID: 26073781 DOI: 10.1016/j.ajhg.2015.05.002

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Singapore Genome Variation Project: a haplotype map of three Southeast Asian populations

Teo YY, Sim X, Ong RT, Tan AK, Chen J, Tantoso E, et al.

Genome Res, 2009 Nov;19(11):2154-62.
PMID: 19700652 DOI: 10.1101/gr.095000.109

The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.

Matched MeSH terms: Genome-Wide Association Study/methods
Fulltext Identification of six new susceptibility loci for invasive epithelial ovarian cancer

Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al.

Nat Genet, 2015 Feb;47(2):164-71.
PMID: 25581431 DOI: 10.1038/ng.3185

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.

Matched MeSH terms: Genome-Wide Association Study/methods*
Fulltext Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk

Lin WY, Camp NJ, Ghoussaini M, Beesley J, Michailidou K, Hopper JL, et al.

Hum Mol Genet, 2015 Jan 01;24(1):285-98.
PMID: 25168388 DOI: 10.1093/hmg/ddu431

Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution

Plissonneau C, Benevenuto J, Mohd-Assaad N, Fouché S, Hartmann FE, Croll D

Front Plant Sci, 2017;8:119.
PMID: 28217138 DOI: 10.3389/fpls.2017.00119

Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

Cross-Disorder Group of the Psychiatric Genomics Consortium

Lancet, 2013 Apr 20;381(9875):1371-9.
PMID: 23453885 DOI: 10.1016/S0140-6736(12)62129-1

BACKGROUND: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.
METHODS: We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples.
FINDINGS: SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers.
INTERPRETATION: Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause.
FUNDING: National Institute of Mental Health.

Matched MeSH terms: Genome-Wide Association Study*
Fulltext Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Cross-Disorder Group of the Psychiatric Genomics Consortium. Electronic address: plee0@mgh.harvard.edu, Cross-Disorder Group of the Psychiatric Genomics Consortium

Cell, 2019 Dec 12;179(7):1469-1482.e11.
PMID: 31835028 DOI: 10.1016/j.cell.2019.11.020

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Matched MeSH terms: Genome-Wide Association Study
Population genetic variation of SLC6A4 gene, associated with neurophysiological development

Hande SH, Krishna SM, Sahote KK, Dev N, Erl TP, Ramakrishna K, et al.

J Genet, 2021;100.
PMID: 33764333

The serotonin transporter 5-HTT is encoded by a single gene SLC6A4. Polymorphisms in SLC6A4 has been associated with a wide variety of neurological and psychiatric disorders including increased risk of posttraumatic stress disorder, higher likelihood for depression, obsessive-compulsive disorder (OCD), increased hostility and criminal behaviour. Genes associated with complex diseases often exhibit strong signatures of purifying selection compared to others. Further, discernible population specific variation in the signature of natural selection have been observed for several complex disease-related genes. In this project we aimed to investigate the population genetic variation of the serotonin transporter gene (SLC6A4), focussing on the single nucleotide polymorphisms (SNPs). To this end, we employed 2504 individuals around the globe available in 1000 Genome project Phase III data and classified them into five ethnic groups: Americans (AMR), Europeans (EUR), Africans (AFR), East Asians (EAS) and South Asians (SAS). Principal component analysis (PCA) performed on all annotated SNPs of SLC6A4 depicted clear clustering between Africans and the rest of the world along PC1, and East Asians and other non-African populations along PC2. Further, these SNPs were found to be under strong selection pressure especially among East Asian populations with significantly high positive cross-population extended haplotype homozygosity scores compared to Africans, indicating that SLC6A4 has likely undergone a strong selective sweep among the East Asians in the recent past. Our study can potentially explain the association between polymorphisms in SLC6A4, and major depression and suicidal tendencies among people of East Asian ancestry and the absence of such associations among people of European ancestry.

Matched MeSH terms: Genome-Wide Association Study
Fulltext Genome-Wide Novel Genic Microsatellite Marker Resource Development and Validation for Genetic Diversity and Population Structure Analysis of Banana

Biswas MK, Bagchi M, Biswas D, Harikrishna JA, Liu Y, Li C, et al.

Genes (Basel), 2020 12 09;11(12).
PMID: 33317074 DOI: 10.3390/genes11121479

Trait tagging through molecular markers is an important molecular breeding tool for crop improvement. SSR markers encoded by functionally relevant parts of a genome are well suited for this task because they may be directly related to traits. However, a limited number of these markers are known for Musa spp. Here, we report 35136 novel functionally relevant SSR markers (FRSMs). Among these, 17,561, 15,373 and 16,286 FRSMs were mapped in-silico to the genomes of Musa acuminata, M. balbisiana and M. schizocarpa, respectively. A set of 273 markers was validated using eight accessions of Musa spp., from which 259 markers (95%) produced a PCR product of the expected size and 203 (74%) were polymorphic. In-silico comparative mapping of FRSMs onto Musa and related species indicated sequence-based orthology and synteny relationships among the chromosomes of Musa and other plant species. Fifteen FRSMs were used to estimate the phylogenetic relationships among 50 banana accessions, and the results revealed that all banana accessions group into two major clusters according to their genomic background. Here, we report the first large-scale development and characterization of functionally relevant Musa SSR markers. We demonstrate their utility for germplasm characterization, genetic diversity studies, and comparative mapping in Musa spp. and other monocot species. The sequences for these novel markers are freely available via a searchable web interface called Musa Marker Database.

Matched MeSH terms: Genome-Wide Association Study/methods
Identification of biomarkers and genetic approaches toward chronic obstructive pulmonary disease

Wadhwa R, Aggarwal T, Malyla V, Kumar N, Gupta G, Chellappan DK, et al.

J Cell Physiol, 2019 08;234(10):16703-16723.
PMID: 30912142 DOI: 10.1002/jcp.28482

Chronic obstructive pulmonary disease accounts as the leading cause of mortality worldwide prominently affected by genetic and environmental factors. The disease is characterized by persistent coughing, breathlessness airways inflammation followed by a decrease in forced expiratory volume1 and exacerbations, which affect the quality of life. Determination of genetic, epigenetic, and oxidant biomarkers to evaluate the progression of disease has proved complicated and challenging. Approaches including exome sequencing, genome-wide association studies, linkage studies, and inheritance and segregation studies played a crucial role in the identification of genes, their pathways and variation in genes. This review highlights multiple approaches for biomarker and gene identification, which can be used for differential diagnosis along with the genome editing tools to study genes associated with the development of disease and models their function. Further, we have discussed the approaches to rectify the abnormal gene functioning of respiratory tissues and various novel gene editing techniques like Zinc finger nucleases (ZFN), transcription activator-like effector nucleases (TALEN), and clustered regulatory interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9).

Matched MeSH terms: Genome-Wide Association Study
Fulltext Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, et al.

Nat Genet, 2020 01;52(1):56-73.
PMID: 31911677 DOI: 10.1038/s41588-019-0537-1

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Matched MeSH terms: Genome-Wide Association Study*
Fulltext Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs)

Darabi H, Beesley J, Droit A, Kar S, Nord S, Moradi Marjaneh M, et al.

Sci Rep, 2016 Sep 07;6:32512.
PMID: 27600471 DOI: 10.1038/srep32512

Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.

Matched MeSH terms: Genome-Wide Association Study

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