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This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.

BackgroundGenetic studies of biomedical phenotypes in underrepresented populations identify disproportionate numbers of novel associations. However, current genomics infrastructure--including most genotyping arrays and sequenced reference panels--best serves populations of European descent. A critical step for facilitating genetic studies in underrepresented populations is to ensure that genetic technologies accurately capture variation in all populations. Here, we quantify the accuracy of low-coverage sequencing in diverse African populations.ResultsWe sequenced the whole genomes of 91 individuals to high-coverage (≥20X) from the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study, in which participants were recruited from Ethiopia, Kenya, South Africa, and Uganda. We empirically tested two data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole genome sequencing data. We show that low-coverage sequencing at a depth of ≥4X captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1X) performed comparable to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation, with 4X sequencing detecting 45% of singletons and 95% of common variants identified in high-coverage African whole genomes.ConclusionThese results indicate that low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, including those that capture variation most common in Europeans and Africans. Low-coverage sequencing effectively identifies novel variation (particularly in underrepresented populations), and presents opportunities to enhance variant discovery at a similar cost to traditional approaches.

BACKGROUNDThere have been considerable recent advances in understanding the genetic architecture of Tourette Syndrome (TS) as well as its underlying neurocircuitry. However, the mechanisms by which genetic variations that increase risk for TS - and its main symptom dimensions - influence relevant brain regions are poorly understood. Here we undertook a genome-wide investigation of the overlap between TS genetic risk and genetic influences on the volume of specific subcortical brain structures that have been implicated in TS.METHODSWe obtained summary statistics for the most recent TS genome-wide association study (GWAS) from the TS Psychiatric Genomics Consortium Working Group (4,644 cases and 8,695 controls) and GWAS of subcortical volumes from the ENIGMA consortium (30,717 individuals). We also undertook analyses using GWAS summary statistics of key symptom factors in TS, namely social disinhibition and symmetry behaviour. SNP Effect Concordance Analysis (SECA) was used to examine genetic pleiotropy - the same SNP affecting two traits - and concordance - the agreement in SNP effect directions across these two traits. In addition, a conditional false discovery rate (FDR) analysis was performed, conditioning the TS risk variants on each of the seven subcortical and the intracranial brain volume GWAS. Linkage Disequilibrium Score Regression (LDSR) was used as validation of SECA.RESULTSSECA revealed significant pleiotropy between TS and putaminal (p=2×10−4) and caudal (p=4×10−4) volumes, independent of direction of effect, and significant concordance between TS and lower thalamic volume (p=1×10−3). LDSR lent additional support for the association between TS and thalamic volume (p=5.85×10−2). Furthermore, SECA revealed significant evidence of concordance between the social disinhibition symptom dimension and lower thalamic volume (p=1×10−3), as well as concordance between symmetry behaviour and greater putaminal volume (p=7×10−4). Conditional FDR analysis further revealed novel variants significantly associated with TS (p−7) when conditioning on intracranial (rs2708146, q=0.046; and rs72853320, q=0.035 and hippocampal (rs1922786, q=0.001 volumes respectively.CONCLUSIONThese data indicate concordance for genetic variations involved in disorder risk and subcortical brain volumes in TS. Further work with larger samples is needed to fully delineate the genetic architecture of these disorders and their underlying neurocircuitry.

Background The genetic architecture of psychotic disorders is complex, with hundreds of genetic risk loci contributing to a polygenic model of disease. Overlap in the genetics of psychotic disorders and brain measures has been found in European populations, but has not been explored in populations of African ancestry. The aim of this study was to determine whether a relationship exists between a schizophrenia-derived PRS and (i) methamphetamine associated psychosis (MAP), and (ii) brain structural measures, in a South African population. Methods The study sample consisted of three participant groups: 31 individuals with MAP, 48 with apsychotic methamphetamine dependence, and 49 healthy controls. Using PRSice, PRS was generated for each of the participants with GWAS summary statistics from the Psychiatric Genomics Consortium Schizophrenia working group (PGC-SCZ2) as the discovery dataset. Regression analyses were performed to determine associations of PRS, with diagnosis, whole brain, and regional gray and white matter measures. Results Schizophrenia-derived PRS did not significantly predict MAP diagnosis. After correction for multiple testing, no significant associations were found between PRS and brain measures across all groups. Discussion The lack of significant associations here may indicate that the study is underpowered, that brain volumes in MAP are due to factors other than polygenic risk for schizophrenia, or that PRS derived from a largely European discovery set has limited utility in individuals of African ancestry. Larger studies, that include diverse populations, and more nuanced brain measures, may help elucidate the relationship between schizophrenia-PRS, brain structural changes, and psychosis. Conclusion This research presents the first PRS study to investigate shared genetic effects across psychotic disorders and brain structural measures in an African population. Ancestrally comparable discovery datasets may be useful for future African genetic research.

Parkinson's disease (PD) is characterised by the loss of dopaminergic neurons in the midbrain. Autosomal recessive, early-onset cases of PD are predominantly caused by mutations in the parkin, PINK1 and DJ-1 genes. Animal and cellular models have verified a direct link between parkin and PINK1, whereby PINK1 phosphorylates and activates parkin at the outer mitochondrial membrane, resulting in removal of dysfunctional mitochondria via mitophagy. Despite the overwhelming evidence for this interaction, few studies have been able to identify a link for DJ-1 with parkin or PINK1. The aim of this review is to summarise the functions of these three proteins, and to analyse the existing evidence for direct and indirect interactions between them. DJ-1 is able to rescue the phenotype of PINK1-knockout Drosophila models, but not of parkin-knockouts, suggesting that DJ-1 may act in a parallel pathway to that of the PINK1/parkin pathway. To further elucidate a commonality between these three proteins, bioinformatics analysis established that Miro (RHOT1) interacts with parkin and PINK1, and HSPA4 interacts with all three proteins. Furthermore, 30 transcription factors were found to be common amongst all three proteins, with many of them being involved in transcriptional regulation. Interestingly, expression of these proteins and their associated transcription factors are found to be significantly down-regulated in PD patients compared to healthy controls. In summary, this review provides insight into common pathways linking three PD-causing genes and highlights some key questions, the answers to which may provide critical insight into the disease process.

Seemingly paradoxical characteristics of psychiatric disorders, including moderate to high prevalence, reduced fecundity, and high heritability have motivated explanations for the persistence of common risk alleles for severe psychiatric phenotypes throughout human evolution. Proposed mechanisms include balancing selection, drift, and weak polygenic adaptation acting either directly, or indirectly through selection on correlated traits. While many mechanisms have been proposed, few have been empirically tested. Leveraging publicly available data of unprecedented sample size, we studied twenty-five traits (i.e., ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical brain structure volume traits, and four complex traits without neuropsychiatric associations) for evidence of several different signatures of selection over a range of evolutionary time scales. Consistent with the largely polygenic architecture of neuropsychiatric traits, we found no enrichment of trait-associated single-nucleotide polymorphisms (SNPs) in regions of the genome that underwent classical selective sweeps (i.e., events which would have driven selected alleles to near fixation). However, we discovered that SNPs associated with some, but not all, behaviors and brain structure volumes are enriched in genomic regions under selection since divergence from Neanderthals ~600,000 years ago, and show further evidence for signatures of ancient and recent polygenic adaptation. Individual subcortical brain structure volumes demonstrate genome-wide evidence in support of a mosaic theory of brain evolution while total intracranial volume and height appear to share evolutionary constraints consistent with concerted evolution. We further characterized the biological processes potentially targeted by selection, through expression Quantitative Trait Locus (eQTL) and Gene Ontology (GO) enrichment analyses and found evidence for the role of regulatory functions among selected SNPs in immune and brain tissues. Taken together, our results suggest that alleles associated with neuropsychiatric, behavioral, and brain volume phenotypes have experienced both ancient and recent polygenic adaptation in human evolution, acting through neurodevelopmental and immune-mediated pathways.

Many of the characteristics of psychiatric disorders, including their early age of onset, moderate to high prevalence (i.e., 1% for schizophrenia, >15% for major depression), reduced fecundity, and high heritability have led many to speculate on how risk alleles have persisted throughout evolutionary history. While several potential mechanisms for maintaining high allele frequency of risk variants have been hypothesized (e.g., weak positive selection, balancing selection), few have been empirically tested. Given the recent analytic advancements in detecting polygenic adaptation, we systematically evaluated evidence for selection across a total of twenty-five complex traits including ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical brain structure volume traits, and four complex traits with no known neuropsychiatric associations. We tested each set of trait-associated variants for evidence of classical hard sweeps (i.e., extreme integrated haplotype scores, iHS), partial sweeps (i.e., extreme population differentiation, Fst), rapid evolution since divergence from Neanderthal (i.e., Neanderthal depletion score, NDS), ancient polygenic selection (i.e., Qx scores), and very recent polygenic selection within the past 2,000 years (i.e., trait singleton density scores, tSDS). Variants associated with schizophrenia (Qx = 208.36, p

Parkinson's disease (PD) is a neurodegenerative disorder characterised by the loss of dopaminergic neurons in the substantia nigra. Mutations in the PINK1 gene result in an autosomal recessive form of early-onset PD. PINK1 plays a vital role in mitochondrial quality control via the removal of dysfunctional mitochondria. The aim of the present study was to create a cellular model of PD using siRNA-mediated knock down of PINK1 in SH-SY5Y neuroblastoma cells The possible protective effects of curcumin, known for its many beneficial properties including antioxidant and anti-inflammatory effects, was tested on this model in the presence and absence of paraquat, an additional stressor. PINK1 siRNA and control cells were separated into four treatment groups: (i) untreated, (ii) treated with paraquat, (iii) pre-treated with curcumin then treated with paraquat, or (iv) treated with curcumin. Various parameters of cellular and mitochondrial function were then measured. The PINK1 siRNA cells exhibited significantly decreased cell viability, mitochondrial membrane potential (MMP), mitochondrial respiration and ATP production, and increased apoptosis. Paraquat-treated cells exhibited decreased cell viability, increased apoptosis, a more fragmented mitochondrial network and decreased MMP. Curcumin pre-treatment followed by paraquat exposure rescued cell viability and increased MMP and mitochondrial respiration in control cells, and significantly decreased apoptosis and increased MMP and maximal respiration in PINK1 siRNA cells. These results highlight a protective effect of curcumin against mitochondrial dysfunction and apoptosis in PINK1-deficient and paraquat-exposed cells. More studies are warranted to further elucidate the potential neuroprotective properties of curcumin.

Parkinson's disease (PD) is a debilitating neurodegenerative disorder with no known cure. PD is prevalent in approximately 1% of individuals aged >65 years, increasing to 4% in individuals aged >80 years. 1 Background. Neurodegenerative disorders such as Parkinson's disease (PD) contribute significantly to global disease burden. PD can be categorised into early-onset PD (EOPD) with an age at onset (AAO) of ≤50 years and late-onset PD (LOPD) with an AAO of >50 years. Aims. To identify factors influencing EOPD and LOPD development in a group of patients in South Africa (SA). Methods. A total of 397 unrelated PD patients were recruited from the Movement Disorders Clinic at Tygerberg Hospital and via the Parkinson's Association of SA. Patient demographic and environmental data were recorded and associations with PD onset (EOPD v. LOPD) were analysed with a Pearson's Chi-squared test. The English- and Afrikaans-speaking (Afrikaner) white patients were analysed separately. Results. Logistic regression analysis showed that ethnicity (p

The molecular basis of Parkinson's disease (PD) has been extensively studied in numerous population groups over the past decade. However, very little is known of the molecular etiology of PD in the South African population. We aimed to assess the genetic contribution of parkin mutations to PD pathology by determining the frequency of both point mutations and exon rearrangements in all 12 exons of the parkin gene in a group of 229 South African patients diagnosed with PD. This was done by performing high resolution melt (HRM) as well as multiplex ligation-dependent probe amplification (MLPA) analyses. In total, seven patients (3.1%; 7/229) had either compound heterozygous or homozygous mutations in parkin, and seven patients (3.1%) had heterozygous sequence variants. Two of the patients with parkin mutations are of Black African ancestry. Reverse-transcription PCR on lymphocytes obtained from two patients verified the presence of parkin mutations on both alleles. In conclusion, the present study reveals that mutations in the parkin gene are not a major contributor to PD in the South African population. Further investigations of the molecular etiology of PD in the unique South African population, particularly the Black African and mixed ancestry sub-populations, are warranted.

Highlights: • Mitochondrial dysfunction observed in patients with parkin-null mutations. • Mitochondrial ATP levels were decreased. • Electron-dense vacuoles were observed in the patients. • Mitochondria from muscle biopsies appeared within normal limits. • One patient did not show these defects possibly due to compensatory mechanisms. - Abstract: Parkinson’s disease (PD), defined as a neurodegenerative disorder, is characterized by the loss of dopaminergic neurons in the substantia nigra in the midbrain. Loss-of-function mutations in the parkin gene are a major cause of autosomal recessive, early-onset PD. Parkin has been implicated in the maintenance of healthy mitochondria, although previous studies show conflicting findings regarding mitochondrial abnormalities in fibroblasts from patients harboring parkin-null mutations. The aim of the present study was to determine whether South African PD patients with parkin mutations exhibit evidence for mitochondrial dysfunction. Fibroblasts were cultured from skin biopsies obtained from three patients with homozygous parkin-null mutations, two heterozygous mutation carriers and two wild-type controls. Muscle biopsies were obtained from two of the patients. The muscle fibers showed subtle abnormalities such as slightly swollen mitochondria in focal areas of the fibers and some folding of the sarcolemma. Although no differences in the degree of mitochondrial network branching were foundmore » in the fibroblasts, ultrastructural abnormalities were observed including the presence of electron-dense vacuoles. Moreover, decreased ATP levels which are consistent with mitochondrial dysfunction were observed in the patients’ fibroblasts compared to controls. Remarkably, these defects did not manifest in one patient, which may be due to possible compensatory mechanisms. These results suggest that parkin-null patients exhibit features of mitochondrial dysfunction. Involvement of mitochondria as a key role player in PD pathogenesis will have important implications for the design of new and more effective therapies.« less