Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms

LIPG-mediated regulation of lipid deposition and proliferation in goat intramuscular preadipocytes involves the PPARα signaling pathway

Endothelial lipase (LIPG), a member of the triglyceride lipase family, plays an essential role in human diseases and lipid metabolism. However, its function in goat intramuscular fat (IMF) deposition remains unclear. In this study, we investigated the role of the LIPG gene in IMF deposition by knocking down and overexpressing it in goat intramuscular preadipocytes. We successfully cloned the full-length LIPG gene, which spans 2,131 bp, including a 94 bp 5' untranslated region (5'UTR), a 1,503 bp coding sequence (CDS), and a 534 bp 3' untranslated region (3'UTR). Tissue expression profiles showed that LIPG is expressed in the heart, liver, spleen, Kidney, longest dorsal muscle, and small intestine tissues of goats. LIPG knockdown significantly inhibited both the proliferation of intramuscular preadipocytes and lipid deposition. Moreover, LIPG knockdown markedly decreased mRNA expression of FASN, LPL, CPT1A, CPT1B, FABP3, while increasing the mRNA expression of ATGL, ACOX1, FADS1, and ELOVL6. These findings were further corroborated through LIPG overexpression experiments. Using RNA sequencing (RNA-seq), we identified 1695 differentially expressed genes (DEGs) between the negative control (NC) and LIPG knockdown (Si-LIPG) groups, with KEGG pathway analysis revealing significant enrichment in the PPAR signaling pathway. Additionally, LIPG knockdown significantly upregulated the expression of both mRNA and protein levels of PPARα. The PPARα agonist WY14643 was able to reverse the enhanced lipid deposition induced by LIPG overexpression. In conclusion, our study highlights a key role for LIPG in the regulation of goat intramuscular preadipocyte proliferation and lipid deposition, potentially through the PPARα signaling pathway. These findings provide new insights into the regulatory mechanisms governing IMF deposition and suggest potential strategies for improving goat meat quality.

Integration of whole-exome sequencing and structural neuroimaging analysis in major depressive disorder: a joint study

Major depressive disorder (MDD) is a common mental illness worldwide and is triggered by an intricate interplay between environmental and genetic factors. Although there are several studies on common variants in MDD, studies on rare variants are relatively limited. In addition, few studies have examined the genetic contributions to neurostructural alterations in MDD using whole-exome sequencing (WES). We performed WES in 367 patients with MDD and 161 healthy controls (HCs) to detect germline and copy number variations in the Korean population. Gene-based rare variants were analyzed to investigate the association between the genes and individuals, followed by neuroimaging-genetic analysis to explore the neural mechanisms underlying the genetic impact in 234 patients with MDD and 135 HCs using diffusion tensor imaging data. We identified 40 MDD-related genes and observed 95 recurrent regions of copy number variations. We also discovered a novel gene, FRMPD3, carrying rare variants that influence MDD. In addition, the single nucleotide polymorphism rs771995197 in the MUC6 gene was significantly associated with the integrity of widespread white matter tracts. Moreover, we identified 918 rare exonic missense variants in genes associated with MDD susceptibility. We postulate that rare variants of FRMPD3 may contribute significantly to MDD, with a mild penetration effect.

The Interaction of LAMA2 and Duration of Illness Affects the Thickness of the Right Transverse Temporal Gyrus in Major Depressive Disorder

Background

Depression is a heritable brain disorder. Laminin genes were recently identified to affect the brain's overall thickness through neurogenesis, differentiation, and migration in depression. This study aims to explore the effects of the LAMA2's single nucleotide polymorphisms (SNP), a subunit gene of laminin, on the detected brain regions of patients with major depressive disorder (MDD).

Methods

The study included 89 patients with MDD and 60 healthy controls with T1-weighted structural magnetic resonance imaging and blood samples for genotyping. The interactions between LAMA2 gene SNPs and diagnosis as well as duration of illness (DOI) were explored on brain measures controlled for age, gender, and site.

Results

The right transverse temporal gyrus and right parahippocampal gyrus showed reduced thickness in MDD. Almost all seven LAMA2 SNPs showed significant interactions with diagnosis on both gyrus (corrected p < 0.05 or trending). In MDD, rs6569604, rs2229848, rs2229849, rs2229850, and rs2784895 interacted with DOI on the right transverse temporal gyrus (corrected p < 0.05), but not the right parahippocampal gyrus.

Conclusion

The thickness of the right transverse temporal gyrus in patients with MDD may be affected by LAMA2 gene and DOI.

Common and rare variant associations with latent traits underlying depression, bipolar disorder, and schizophrenia

Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants' responses. We calculated participants' scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05-1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case-control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10-9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.

Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach.

METHODS

We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339).

RESULTS

We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10^-9) and CTNNA2 (rs6729523, p = 1.25 × 10^-8). The gene-based analysis revealed another six genes (p < 2.703 × 10^-6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort.

CONCLUSIONS

Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

The genetic basis of major depression

Major depressive disorder (MDD) is a common, debilitating, phenotypically heterogeneous disorder with heritability ranges from 30% to 50%. Compared to other psychiatric disorders, its high prevalence, moderate heritability, and strong polygenicity have posed major challenges for gene-mapping in MDD. Studies of common genetic variation in MDD, driven by large international collaborations such as the Psychiatric Genomics Consortium, have confirmed the highly polygenic nature of the disorder and implicated over 100 genetic risk loci to date. Rare copy number variants associated with MDD risk were also recently identified. The goal of this review is to present a broad picture of our current understanding of the epidemiology, genetic epidemiology, molecular genetics, and gene-environment interplay in MDD. Insights into the impact of genetic factors on the aetiology of this complex disorder hold great promise for improving clinical care.

Analysis of 200 000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of developing a mood disorder resulting in psychiatric referral

BACKGROUND

Depression is moderately heritable but there is no common genetic variant which has a major effect on susceptibility. A previous analysis of 50 000 exome-sequenced subjects failed to implicate any genes or sets of genes in which rare variants were associated with risk of affective disorder requiring specialist treatment. A much larger exome-sequenced dataset is now available.

METHODS

Data from 200 632 exome-sequenced UK Biobank participants was analysed. Subjects were treated as cases if they had reported having seen a psychiatrist for 'nerves, anxiety, tension or depression'. Gene-wise weighted burden analysis was performed to see if there were any genes or sets of genes for which there was an excess of rare, functional variants in cases.

RESULTS

There were 22 886 cases and 176 486 controls. There were 22 642 informative genes but no gene or gene set produced a statistically significant result after correction for multiple testing. None of the genes or gene sets with the lowest P values appeared to be an obvious biological candidate.

CONCLUSIONS

The results conform exactly with the expectation under the null hypothesis. It seems unlikely that the use of common, poorly defined phenotypes will produce useful advances in understanding genetic contributions to affective disorder and it might be preferable to focus instead on obtaining large exome-sequenced samples of conditions such as bipolar 1 disorder and severe, recurrent depression. This research has been conducted using the UK Biobank Resource.

Targeted sequencing of the BDNF gene in young Chinese Han people with major depressive disorder

BACKGROUND

Adolescence and young adulthood are considered the peak age for the emergence of many psychiatric disorders, in particular major depressive disorder (MDD). Previous research has shown substantial heritability for MDD. In addition, the brain-derived neurotrophic factor (BDNF) gene is known to be associated with MDD. However, there has been no study conducting targeted sequencing of the BDNF gene in young MDD patients so far.

METHOD

To examine whether the BDNF gene is associated with the occurrence of MDD in young patients, we used targeted sequencing to detect the BDNF gene variants in 259 young Chinese Han people (105 MDD patients and 154 healthy subjects).

RESULTS

The BDNF variant rs4030470 was associated with MDD in young Chinese Han people (uncorrected p = 0.046), but this was no longer significant after applying FDR correction (p = 0.552, after FDR correction). We did not find any significant differences in genotype or haplotype frequencies between the case and control groups, and furthermore discovered no rare mutation variants any of the 259 subjects.

CONCLUSION

Our results do not support an association of the BDNF gene variants with MDD in young people in the Chinese Han population.

Insights into the genomics of affective disorders

Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression.

Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

Sex differences in the genetic architecture of depression

The prevalence and clinical characteristics of depressive disorders differ between women and men; however, the genetic contribution to sex differences in depressive disorders has not been elucidated. To evaluate sex-specific differences in the genetic architecture of depression, whole exome sequencing of samples from 1000 patients (70.7% female) with depressive disorder was conducted. Control data from healthy individuals with no psychiatric disorder (n = 72, 26.4% female) and East-Asian subpopulation 1000 Genome Project data (n = 207, 50.7% female) were included. The genetic variation between men and women was directly compared using both qualitative and quantitative research designs. Qualitative analysis identified five genetic markers potentially associated with increased risk of depressive disorder in females, including three variants (rs201432982 within PDE4A, and rs62640397 and rs79442975 within FDX1L) mapping to chromosome 19p13.2 and two novel variants (rs820182 and rs820148) within MYO15B at the chromosome 17p25.1 locus. Depressed patients homozygous for these variants showed more severe depressive symptoms and higher suicidality than those who were not homozygotes (i.e., heterozygotes and homozygotes for the non-associated allele). Quantitative analysis demonstrated that the genetic burden of protein-truncating and deleterious variants was higher in males than females, even after permutation testing. Our study provides novel genetic evidence that the higher prevalence of depressive disorders in women may be attributable to inherited variants.

Integrating Metabolomics, Genomics, and Disease Pathways in Age-Related Macular Degeneration: The EYE-RISK Consortium

PURPOSE

The current study aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date, as well as aiming to determine the effect of AMD-associated genetic variants on metabolite levels and investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways.

DESIGN

Case-control association analysis of metabolomics data.

PARTICIPANTS

Five European cohorts consisting of 2267 AMD patients and 4266 control participants.

METHODS

Metabolomics was performed using a high-throughput proton nuclear magnetic resonance metabolomics platform, which allows quantification of 146 metabolite measurements and 79 derivative values. Metabolome-AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d-to-C3 ratio) were investigated using linear regression.

MAIN OUTCOME MEASURES

Metabolites associated with AMD.

RESULTS

We identified 60 metabolites that were associated significantly with AMD, including increased levels of large and extra-large high-density lipoprotein (HDL) subclasses and decreased levels of very low-density lipoprotein (VLDL), amino acids, and citrate. Of 52 AMD-associated genetic variants, 7 variants were associated significantly with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, and LIPC) with metabolites belonging to the large and extra-large HDL subclasses. Also, 57 of 60 metabolites were associated significantly with complement activation levels, independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation.

CONCLUSIONS

Lipoprotein levels were associated with AMD-associated genetic variants, whereas decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD.

Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation

Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.

Genotype- and Phenotype-Based Subgroups in Geographic Atrophy Secondary to Age-Related Macular Degeneration: The EYE-RISK Consortium

PURPOSE

Geographic atrophy (GA) secondary to age-related macular degeneration is considered a single entity. This study aimed to determine whether GA subgroups exist that can be defined by their genotype and phenotype.

DESIGN

Retrospective analysis of cross-sectional data.

PARTICIPANTS

Individuals (196 eyes of 196 patients) 50 years of age or older with GA from the EYE-RISK database.

METHODS

Participants were graded for the presence of each of the following fundus features on color fundus photography: large soft drusen, reticular pseudodrusen (RPD), refractile drusen, hyperpigmentation, location of atrophy (foveal vs. extrafoveal), and multifocal lesions. Genotypes of 33 single nucleotide polymorphisms previously assigned to the complement, lipid metabolism, or extracellular matrix (ECM) pathways and ARMS2 also were included, and genetic risk scores (GRSs) for each of those 3 pathways were calculated. Hierarchical cluster analysis was used to determine subgroups of participants defined by these features. The discriminative ability of genotype, phenotype, or both for each subgroup was determined with 10-fold cross-validated areas under the receiver operating characteristic curve (cvAUCs), and the agreement between predicted and actual subgroup membership was assessed with calibration plots.

MAIN OUTCOME MEASURES

Identification and characterization of GA subgroups based on their phenotype and genotype.

RESULTS

Cluster analyses identified 3 subgroups of GA. Subgroup 1 was characterized by high complement GRS, frequently associated with large soft drusen and foveal atrophy; subgroup 2 generally showed low GRS, foveal atrophy, and few drusen (any type); and subgroup 3 showed a high ARMS2 and ECM GRS, RPD, and extrafoveal atrophy. A high discriminative ability existed between subgroups for the genotype (cvAUC, ≥0.94), and a modest discriminative ability existed for the phenotype (cvAUC, <0.65), with good calibration.

CONCLUSIONS

We identified 3 GA subgroups that differed mostly by their genotype. Atrophy location and drusen type were the most relevant phenotypic features.

Exome Sequencing Analysis Identifies Rare Variants in ATM and RPL8 That Are Associated With Shorter Telomere Length

Telomeres are important for maintaining genomic stability. Telomere length has been associated with aging, disease, and mortality and is highly heritable (∼82%). In this study, we aimed to identify rare genetic variants associated with telomere length using whole-exome sequence data. We studied 1,303 participants of the Erasmus Rucphen Family (ERF) study, 1,259 of the Rotterdam Study (RS), and 674 of the British Heart Foundation Family Heart Study (BHF-FHS). We conducted two analyses, first we analyzed the family-based ERF study and used the RS and BHF-FHS for replication. Second, we combined the summary data of the three studies in a meta-analysis. Telomere length was measured by quantitative polymerase chain reaction in blood. We identified nine rare variants significantly associated with telomere length (p-value < 1.42 × 10^–7, minor allele frequency of 0.2–0.5%) in the ERF study. Eight of these variants (in C11orf65, ACAT1, NPAT, ATM, KDELC2, and EXPH5) were located on chromosome 11q22.3 that contains ATM, a gene involved in telomere maintenance. Although we were unable to replicate the variants in the RS and BHF-FHS (p-value ≥ 0.21), segregation analysis showed that all variants segregate with shorter telomere length in a family. In the meta-analysis of all studies, a nominally significant association with LTL was observed with a rare variant in RPL8 (p-value = 1.48 × 10⁻⁶), which has previously been associated with age. Additionally, a novel rare variant in the known RTEL1 locus showed suggestive evidence for association (p-value = 1.18 × 10^–4) with LTL. To conclude, we identified novel rare variants associated with telomere length. Larger samples size are needed to confirm these findings and to identify additional variants.

A study combining whole-exome sequencing and structural neuroimaging analysis for major depressive disorder

BACKGROUND

Genetic variations associated with major depressive disorder (MDD) may affect the structural aspects of neural networks mediated by the molecular pathways involved in neuronal survival and synaptic plasticity. However, few studies have applied a novel approach such as whole-exome sequencing (WES) analysis to investigate the genetic contribution to the neurostructural changes in MDD.

METHODS

In the first part of the study, we investigated rare variants of selected genes from previous WES studies using a WES analysis in 184 patients with MDD and 82 healthy controls. In the second part of the study, we explored the association between the common genetic variants from the WES analysis and cortical thickness in 91 patients with MDD and 75 healthy controls. The gray-matter thickness of each cortical region was measured using FreeSurfer.

RESULTS

We identified recurrent non-silent variants in 24 MDD-related genes including FASN, MYH13, UNC13D, LILRA1, CACNA1B, TRIO, HOMER3, and BCAR3, and observed eleven recurrently altered copy number alternations where a gain on 15q11.2 and losses on 7q34 and 15q11.1-q11.2 in MDD genomes. We also found that rs11592462 in CDH23, a calcium-dependent cell-adhesion molecule encoding gene, was significantly associated with thinning in the right anterior cingulate cortex.

LIMITATION

The small sample size may lead our findings to be underpowered regarding rare variants.

CONCLUSION

The present study identified that non-synonymous rare variants were significantly associated with risk of MDD and found that genetic contributions to the development of MDD may be mediated by alterations in cortical thickness of emotion-processing neural circuits.

Variants in the Upstream Region of the Insulin Receptor Substrate-1 Gene Is Associated with Major Depressive Disorder in the Han Chinese Population

INTRODUCTION

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders, although its underlying genetic mechanism remains unknown. Insulin receptor substrate-1 (IRS-1) is one of the critical downstream molecules in the insulin resistance signaling pathway, linking depression and diabetes. Therefore, we hypothesized that IRS-1 would be a susceptible gene for MDD, and we aimed to examine the genetic association between IRS-1 and MDD.

METHODS

This case-control study included 583 patients with MDD and 564 controls, and the genotypic and allelic distributions of the IRS-1 gene's four single nucleotide polymorphisms (SNPs) were detected by TaqMan SNP genotyping technology. Of the 583 patients, 191 underwent a further detailed interview about symptom severity and family history of mental illness. The chi-square or t test was used to analyze the data, and analyses were performed using SPSS19.0 software.

RESULTS

A haplotype in the 5'-upstream region of IRS-1 consisting of rs13411764 and rs3820926 was a risk factor of MDD. Patients with a family history of mental illness were more likely to have a GG genotype in rs13411764 and a G-T haplotype containing rs13411714-rs3820926.

DISCUSSION

The findings imply that the haplotype consisting of rs13411764 and rs3820926 in the upstream of IRS-1 is a risk factor for MDD. This haplotype could affect IRS-1 expression levels, and it is mostly inherited from parents. Thus, the presence of variants in the upstream region of IRS-1 is a risk factor of MDD, and this study could serve as a convincing reference for further studies.

Genetic Advance in Depressive Disorder

Major depressive disorder (MDD) and bipolar disorder (BPD) are both chronic, severe mood disorder with high misdiagnosis rate, leading to substantial health and economic burdens to patients around the world. There is a high misdiagnosis rate of bipolar depression (BD) just based on symptomology in depressed patients whose previous manic or mixed episodes have not been well recognized. Therefore, it is important for psychiatrists to identify these two major psychiatric disorders. Recently, with the accumulation of clinical sample sizes and the advances of methodology and technology, certain progress in the genetics of major depression and bipolar disorder has been made. This article reviews the candidate genes for MDD and BD, genetic variation loci, chromosome structural variation, new technologies, and new methods.

Rare variants in SLC6A4 cause susceptibility to major depressive disorder with suicidal ideation in Han Chinese adolescents and young adults

BACKGROUND

Suicidal ideation (SI) is the most serious symptom of major depressive disorder (MDD) and considered an extreme state. The serotonin transporter gene (SLC6A4) plays a significant role in MDD and suicide pathophysiology. Previous studies have revealed an association between common variants of SLC6A4 with the risk of MDD and suicide. However, very few studies have so far focused on the degree to which rare variants of SLC6A4 are responsible for the depression observed in adolescent and young adult suicide patients. The aim of this study was to examine the impact of common and rare variants of SLC6A4 on the risk of Han Chinese adolescents and young adults suffering MDD with SI.

METHODS

Targeted sequencing of the SLC6A4 gene was conducted using FastTarget technology in Han Chinese adolescents and young adults, of which 74 were MDD patients with SI and 150 were healthy controls. Gene-based association analyses of rare variants were performed using enrichment analysis and a cumulative allele test. An allele association study was performed against common variants.

RESULTS

After sequencing and bioinformatics analysis, a total of 15 single nucleotide variants (SNVs) were detected in the targeted regions from all participants, including 9 common and 6 rare variants. Among these, 5 rare variants were identified within the study group. Enrichment analysis of rare variants demonstrated a statistical difference (p = 0.042) between the study and control groups. Using cumulative allele analysis, alternative alleles in the SLC6A4 gene exhibited an association with MDD patients with SI (cumulative allele: OR = 10.18, 95% CI = 1.18-87.32, p = 0.017). No significant association was found between the 9 common SLC6A4 variants and MDD patients with SI.

CONCLUSIONS

Our results suggest that rare variants of SLC6A4 may contribute to a genetic risk of adolescents and young adults suffering MDD with SI.

Genetic basis of depressive disorders

Depression is a common mental disorder being one of the main causes of disability and mortality worldwide. Despite an intensive research during the past decades, the etiology of depressive disorders (DDs) remains incompletely understood; however, genetic factors are significantly involved in the liability to depression. The present review is focused on the studies based on a candidate gene approach, genome-wide association studies (GWAS) and whole exome sequencing (WES), which previously demonstrated associations between gene polymorphisms and DDs. According to the first approach, DD development is affected by serotonergic (TPH1, TPH2, HTR1A, HTR2A, and SLC6A4), dopaminergic (DRD4, SLC6A3) and noradrenergic (SLC6A2) system genes, and genes of enzymatic degradation (MAOA, COMT). In addition, there is evidence of the involvement of HPA-axis genes (OXTR, AVPR1A, and AVPR1B), sex hormone receptors genes (ESR1, ESR2, and AR), neurotrophin (BDNF) and methylenetetrahydrofolate reductase (MTHFR) genes, neuronal apoptosis (CASP3, BCL-XL, BAX, NPY, APP, and GRIN1) and inflammatory system (TNF, CRP, IL6, IL1B, PSMB4, PSMD9, and STAT3) genes in DD development. The results of the second approach (GWAS and WES) revealed that the PCLO, SIRT1, GNL3, GLT8D1, ITIH3, MTNR1A, BMP5, FHIT, KSR2, PCDH9, and AUTS2 genes predominantly responsible for neurogenesis and cell adhesion are involved in liability to depression. Therefore, the findings discussed suggest that genetic liability to DD is a complex process, which assumes simultaneous functioning of multiple genes including those reported previously, and requires future research in this field.

 

Association of plasma endothelial lipase levels on cognitive impairment

BACKGROUND

Peripheral high-density lipoprotein cholesterol (HDL-C) has been known to influx into the brain and be inversely associated with the risk of Alzheimer's disease (AD). However, recent prospective studies of the association between HDL-C and AD have yielded inconsistent results. Here, we examined the association between the endothelial lipase (EL), which is known to be major determinant of HDL-C levels, and cognitive function.

METHOD

We compared plasma from 20 patients with Alzheimer's disease (AD), 38 persons with mild cognitive impairment, and 51 cognitively normal controls. Plasma EL levels were measured using the enzyme-linked immunosorbent assay.

RESULTS

EL levels were inversely correlated with HDL-C, as previously reported; however, there were no mean differences in plasma EL between the diagnostic groups. An analysis by classification of dementia severity according to clinical dementia rating (CDR) showed that the EL levels were significantly higher in the CDR1 group (mild dementia), as compared to CDR0 (no dementia), CDR0.5 (very mild), and CDR2 (moderate) groups. Prior to moderate dementia stage, trends analysis showed that EL levels tended to increase with increasing severity (p for trend = 0.013). Consistently, elevated EL levels were significantly correlated with the mini-mental state examination (MMSE) score (r = - 0.29, p = 0.003). Logistic regression for association between plasma EL and cognitive impairment (MMSE score ≤ 25) showed that participants with EL levels in the upper range (> 31.6 ng/ml) have a higher adjusted odds ratio of cognitive impairment than those within the lower EL range.

CONCLUSION

Findings from the present study reflect the association of EL and cognition, suggesting that the individuals with elevated plasma EL concentration are at an increased risk of cognitive impairment.

[Breakthrough in understanding the molecular causes of psychiatric disorders]

A long-established hypothesis is that genetic factors contribute to the development of psychiatric diseases, including common illnesses such as schizophrenia and the affective disorders; however, reliable molecular identification of these factors represents a far more recent innovation. This has been rendered possible by technological advances in the individual characterization of the human genome and the combining of large genetic datasets at the international level. For the first time, the results of genome-wide analyses provide researchers with systematic insights into disease-relevant biological mechanisms. Here, the integrated analysis of different omics level data generates important insights into the functional interpretation of the genetic findings. The results of genetic studies also demonstrated the degree of etiological overlap between differing psychiatric disorders, with the greatest commonality having been observed to date between schizophrenia and bipolar affective disorder. Although the translation of genetic findings into routine clinical practice is being pursued at various levels, elaborate follow-up studies are typically necessary. The diagnostic investigation of rare genomic deletions/duplications (so-called copy number variants) in patients with schizophrenia is likely to represent one of the first examples of routine clinical application. The necessary prerequisites for this are currently being defined.

Genetic effects on white matter integrity in drug-naive patients with major depressive disorder: a diffusion tensor imaging study of 17 genetic loci associated with depressive symptoms

BACKGROUND

A genome-wide association study using megadata identified 17 single-nucleotide polymorphisms (SNPs) in candidate genes for major depressive disorder (MDD). These MDD susceptibility polymorphisms may affect white matter (WM) integrity. This study aimed to investigate the relationship between WM alterations and 17 SNPs in candidate genes for MDD in the first depressive episode of drug-naive MDD patients using a tract-based spatial statistics (TBSS) method.

METHODS

Thirty-five drug-naive MDD patients with a first depressive episode and 47 age-and sex-matched healthy subjects underwent diffusion tensor imaging scans and genotyping. The genotype-diagnosis interactions related to WM integrity were evaluated using TBSS for the 17 SNPs.

RESULTS

For the anterior thalamic radiation, cingulum, corticospinal tract, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, uncinate fasciculus, forceps major, and forceps minor, the genotype effect significantly differed between diagnosis groups (P<0.05, family-wise error corrected) in only one SNP, rs301806, in the arginine-glutamic acid dipeptide (RE) repeats (RERE) gene.

CONCLUSION

The RERE polymorphism was associated with WM alterations in first-episode and drug-naive MDD patients, which may be at least partially related to the manifestation of MDD. Future studies are needed to explore the gene-environment interactions with regard to individual WM integrity.

Genetic Markers in Psychiatry

Psychiatric disorders such as addiction (substance use and addictive disorders), depression, eating disorders, schizophrenia, and post-traumatic stress disorder (PTSD) are severe, complex, multifactorial mental disorders that carry a high social impact, enormous public health costs, and various comorbidities as well as premature morbidity. Their neurobiological foundation is still not clear. Therefore, it is difficult to uncover new set of genes and possible genetic markers of these disorders since the understanding of the molecular imbalance leading to these disorders is not complete. The integrative approach is needed which will combine genomics and epigenomics; evaluate epigenetic influence on genes and their influence on neuropeptides, neurotransmitters, and hormones; examine gene × gene and gene × environment interplay; and identify abnormalities contributing to development of these disorders. Therefore, novel genetic approaches based on systems biology focused on improvement of the identification of the biological underpinnings might offer genetic markers of addiction, depression, eating disorders, schizophrenia, and PTSD. These markers might be used for early prediction, detection of the risk to develop these disorders, novel subtypes of the diseases and tailored, personalized approach to therapy.

Whole-Genome Linkage Scan Combined With Exome Sequencing Identifies Novel Candidate Genes for Carotid Intima-Media Thickness

Carotid intima-media thickness (cIMT) is an established heritable marker for subclinical atherosclerosis. In this study, we aim to identify rare variants with large effects driving differences in cIMT by performing genome-wide linkage analysis of individuals in the extremes of cIMT trait distribution (>90th percentile) in a large family-based study from a genetically isolated population in the Netherlands. Linked regions were subsequently explored by fine-mapping using exome sequencing. We observed significant evidence of linkage on chromosomes 2p16.3 [rs1017418, heterogeneity LOD (HLOD) = 3.35], 19q13.43 (rs3499, HLOD = 9.09), 20p13 (rs1434789, HLOD = 4.10), and 21q22.12 (rs2834949, HLOD = 3.59). Fine-mapping using exome sequencing data identified a non-coding variant (rs62165235) in PNPT1 gene under the linkage peak at chromosome 2 that is likely to have a regulatory function. The variant was associated with quantitative cIMT in the family-based study population (effect = 0.27, p-value = 0.013). Furthermore, we identified several genes under the linkage peak at chromosome 21 highly expressed in tissues relevant for atherosclerosis. To conclude, our linkage analysis identified four genomic regions significantly linked to cIMT. Further analyses are needed to demonstrate involvement of identified candidate genes in development of atherosclerosis.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

A rare missense variant in RCL1 segregates with depression in extended families

Depression is the most prevalent psychiatric disorder with a complex and elusive etiology that is moderately heritable. Identification of genes would greatly facilitate the elucidation of the biological mechanisms underlying depression, however, its complex etiology has proved to be a major bottleneck in the identification of its genetic risk factors, especially in genome-wide association-like studies. In this study, we exploit the properties of a genetic isolate and its family-based structure to explore whether relatively rare exonic variants influence the burden of depressive symptoms in families. Using a multistep approach involving linkage and haplotype analyses followed by exome sequencing in the Erasmus Rucphen Family (ERF) study, we identified a rare (minor allele frequency (MAF)=1%) missense c.1114C>T mutation (rs115482041) in the RCL1 gene segregating with depression across multiple generations. Rs115482041 showed significant association with depressive symptoms (N=2393, βT-allele=2.33, P-value=1 × 10-4) and explained 2.9% of the estimated genetic variance of depressive symptoms (22%) in ERF. Despite being twice as rare (MAF<0.5%), c.1114C>T showed similar effect and significant association with depressive symptoms in samples from the independent population-based Rotterdam study (N=1604, βT-allele=3.60, P-value=3 × 10-2). A comparison of RCL1 expression in human and mouse brain revealed a striking co-localization of RCL1 with the layer 1 interlaminar subclass of astrocytes found exclusively in higher-order primates. Our findings identify RCL1 as a novel candidate gene for depression and offer insights into mechanisms through which RCL1 may be relevant for depression.

Investigation of short tandem repeats in major depression using whole-genome sequencing data

BACKGROUND

Major depressive disorder (MDD) is a leading contributor to global disease burden. Recent studies have shown that genetic factors play significant roles in the susceptibility to this condition; however, the underlying genetic basis currently remains largely unknown. Short tandem repeat (STR) has been proposed as an explanatory factor in the "missing heritability" of complex diseases or traits.

METHODS

We investigated STR variations from 15 MDD patients and 10 ethnically matched healthy controls based on their deep whole-genome sequencing (WGS) data. The lobSTR software was used to computationally determine STRs.

RESULTS

The results of the Mexican-American sample showed that STRs are significantly richer in healthy controls than in MDD cases on each of the 23 chromosomes (all false discovery rates, FDR P-values < 0.0062); while for the Australian of European-ancestry sample, there was no statistically significant STRs difference between MDD cases and controls.

LIMITATIONS

High quality WGS costs limited obtaining larger datasets.

CONCLUSIONS

This preliminary work is the first study that STR variations are applied to investigate MDD based on WGS data. The results on Mexican-American population may imply that within the same ancestry, targeted sequencing on a specific chromosome or region of genome would be sufficient for examining the relationship between STR and MDD. Further studies should examine larger sequencing datasets on other ethnic groups.

Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the "missing heritability" by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the "missing heritability" of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e-16) and rare SNP set (P value = 7.681e-12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD.

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders.

Progress in Genetic Studies of Tourette's Syndrome

Tourette's Syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progresses in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES) and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.

Exome-Wide Meta-Analysis Identifies Rare 3'-UTR Variant in ERCC1/CD3EAP Associated with Symptoms of Sleep Apnea

Obstructive sleep apnea (OSA) is a common sleep breathing disorder associated with an increased risk of cardiovascular and cerebrovascular diseases and mortality. Although OSA is fairly heritable (~40%), there have been only few studies looking into the genetics of OSA. In the present study, we aimed to identify genetic variants associated with symptoms of sleep apnea by performing a whole-exome sequence meta-analysis of symptoms of sleep apnea in 1,475 individuals of European descent. We identified 17 rare genetic variants with at least suggestive evidence of significance. Replication in an independent dataset confirmed the association of a rare genetic variant (rs2229918; minor allele frequency = 0.3%) with symptoms of sleep apnea (p-value_meta = 6.98 × 10⁻⁹, β_meta = 0.99). Rs2229918 overlaps with the 3′ untranslated regions of ERCC1 and CD3EAP genes on chromosome 19q13. Both genes are expressed in tissues in the neck area, such as the tongue, muscles, cartilage and the trachea. Further, CD3EAP is localized in the nucleus and mitochondria and involved in the tumor necrosis factor-alpha/nuclear factor kappa B signaling pathway. Our results and biological functions of CD3EAP/ERCC1 genes suggest that the 19q13 locus is interesting for further OSA research.

The PHF21B gene is associated with major depression and modulates the stress response

Major depressive disorder (MDD) affects around 350 million people worldwide; however, the underlying genetic basis remains largely unknown. In this study, we took into account that MDD is a gene-environment disorder, in which stress is a critical component, and used whole-genome screening of functional variants to investigate the 'missing heritability' in MDD. Genome-wide association studies (GWAS) using single- and multi-locus linear mixed-effect models were performed in a Los Angeles Mexican-American cohort (196 controls, 203 MDD) and in a replication European-ancestry cohort (499 controls, 473 MDD). Our analyses took into consideration the stress levels in the control populations. The Mexican-American controls, comprised primarily of recent immigrants, had high levels of stress due to acculturation issues and the European-ancestry controls with high stress levels were given higher weights in our analysis. We identified 44 common and rare functional variants associated with mild to moderate MDD in the Mexican-American cohort (genome-wide false discovery rate, FDR, <0.05), and their pathway analysis revealed that the three top overrepresented Gene Ontology (GO) processes were innate immune response, glutamate receptor signaling and detection of chemical stimulus in smell sensory perception. Rare variant analysis replicated the association of the PHF21B gene in the ethnically unrelated European-ancestry cohort. The TRPM2 gene, previously implicated in mood disorders, may also be considered replicated by our analyses. Whole-genome sequencing analyses of a subset of the cohorts revealed that European-ancestry individuals have a significantly reduced (50%) number of single nucleotide variants compared with Mexican-American individuals, and for this reason the role of rare variants may vary across populations. PHF21b variants contribute significantly to differences in the levels of expression of this gene in several brain areas, including the hippocampus. Furthermore, using an animal model of stress, we found that Phf21b hippocampal gene expression is significantly decreased in animals resilient to chronic restraint stress when compared with non-chronically stressed animals. Together, our results reveal that including stress level data enables the identification of novel rare functional variants associated with MDD.

Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression

Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.

A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort

Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.

A novel strategy for clustering major depression individuals using whole-genome sequencing variant data

Major depressive disorder (MDD) is highly prevalent, resulting in an exceedingly high disease burden. The identification of generic risk factors could lead to advance prevention and therapeutics. Current approaches examine genotyping data to identify specific variations between cases and controls. Compared to genotyping, whole-genome sequencing (WGS) allows for the detection of private mutations. In this proof-of-concept study, we establish a conceptually novel computational approach that clusters subjects based on the entirety of their WGS. Those clusters predicted MDD diagnosis. This strategy yielded encouraging results, showing that depressed Mexican-American participants were grouped closer; in contrast ethnically-matched controls grouped away from MDD patients. This implies that within the same ancestry, the WGS data of an individual can be used to check whether this individual is within or closer to MDD subjects or to controls. We propose a novel strategy to apply WGS data to clinical medicine by facilitating diagnosis through genetic clustering. Further studies utilising our method should examine larger WGS datasets on other ethnical groups.