NDVI changes in the Arctic: Functional significance in the moist acidic tundra of Northern Alaska.

The Normalized Difference Vegetation Index (NDVI), derived from reflected visible and infrared radiation, has been critical to understanding change across the Arctic, but relatively few ground truthing efforts have directly linked NDVI to structural and functional properties of Arctic tundra ecosystems. To improve the interpretation of changing NDVI within moist acidic tundra (MAT), a common Arctic ecosystem, we coupled measurements of NDVI, vegetation structure, and CO2 flux in seventy MAT plots, chosen to represent the full range of typical MAT vegetation conditions, over two growing seasons. Light-saturated photosynthesis, ecosystem respiration, and net ecosystem CO2 exchange were well predicted by NDVI, but not by vertically-projected leaf area, our nondestructive proxy for leaf area index (LAI). Further, our data indicate that NDVI in this ecosystem is driven primarily by the biochemical properties of the canopy leaves of the dominant plant functional types, rather than purely the amount of leaf area; NDVI was more strongly correlated with top cover and repeated cover of deciduous shrubs than other plant functional types, a finding supported by our data from separate "monotypic" plots. In these pure stands of a plant functional type, deciduous shrubs exhibited higher NDVI than any other plant functional type. Likewise, leaves from the two most common deciduous shrubs, Betula nana and Salix pulchra, exhibited higher leaf-level NDVI than those from the codominant graminoid, Eriophorum vaginatum. Our findings suggest that recent increases in NDVI in MAT in the North American Arctic are largely driven by expanding deciduous shrub canopies, with substantial implications for MAT ecosystem function, especially net carbon uptake.

Dysregulation of synaptic and developmental transcriptomic/proteomic profiles upon depletion of MUNC18-1.

Absence of presynaptic protein MUNC18-1 (gene: Stxbp1) leads to neuronal cell death at an immature stage before synapse formation. Here, we performed transcriptomic and proteomic profiling of immature Stxbp1 knockout (KO) cells to discover which cellular processes depend on MUNC18-1. Hippocampi of Stxbp1 KO mice showed cell-type specific dysregulation of 2123 transcripts primarily related to synaptic transmission and immune response. To further investigate direct, neuron-specific effects of MUNC18-1 depletion, a proteomic screen was performed on murine neuronal cultures at two developmental timepoints prior to onset of neuron degeneration. 399 proteins were differentially expressed, which were primarily involved in synaptic function (especially synaptic vesicle exocytosis) and neuron development. We further show that many of the downregulated proteins upon loss of MUNC18-1 are normally upregulated during this developmental stage. Thus, absence of MUNC18-1 extensively dysregulates the transcriptome and proteome, primarily affecting synaptic and developmental profiles. Lack of synaptic activity is unlikely to underlie these effects, as the changes were observed in immature neurons without functional synapses, and minimal overlap was found to activity-dependent proteins. We hypothesize that presence of MUNC18-1 is essential to advance neuron development, serving as a 'checkpoint' for neurons to initiate cell death in its absence.Significance StatementPresynaptic protein MUNC18-1 is essential for neuronal functioning. Pathogenic variants in its gene, STXBP1, are among the most common found in patients with developmental delay and epilepsy. To discern the pathogenesis in these patients, a thorough understanding of MUNC18-1's function in neurons is required. Here, we show that loss of MUNC18-1 results in extensive dysregulation of synaptic and developmental proteins in immature neurons before synapse formation. Many of the downregulated proteins are normally upregulated during this developmental stage. This indicates that MUNC18-1 is a critical regulator of neuronal development, which could play an important role in the pathogenesis of STXBP1 variant carriers.

Technological readiness and implementation of genomic-driven precision medicine for complex diseases.

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

Stitching the synapse: Cross-linking mass spectrometry into resolving synaptic protein interactions.

Synaptic transmission is the predominant form of communication in the brain. It requires functionally specialized molecular machineries constituted by thousands of interacting synaptic proteins. Here, we made use of recent advances in cross-linking mass spectrometry (XL-MS) in combination with biochemical and computational approaches to reveal the architecture and assembly of synaptic protein complexes from mouse brain hippocampus and cerebellum. We obtained 11,999 unique lysine-lysine cross-links, comprising connections within and between 2362 proteins. This extensive collection was the basis to identify novel protein partners, to model protein conformational dynamics, and to delineate within and between protein interactions of main synaptic constituents, such as Camk2, the AMPA-type glutamate receptor, and associated proteins. Using XL-MS, we generated a protein interaction resource that we made easily accessible via a web-based platform (http://xlink.cncr.nl) to provide new entries into exploration of all protein interactions identified.

Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies.

To identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic heterogeneity through selecting more homogenous MDD subtypes. The value of these strategies has been debated. In this review, we summarize the most recent findings of large genomic studies that applied these approaches, and we highlight the merits and pitfalls of both approaches with particular attention to methodological and psychometric issues. We also discuss the results of analyses that investigated the heterogeneity of MDD. We conclude that both study designs are essential for further research. So far, increasing sample size has led to the identification of a relatively high number of genomic loci linked to depression. However, part of the identified variants may be related to a phenotype common to internalizing disorders and related traits. As such, samples containing detailed clinical information are needed to dissect depression heterogeneity and enable the potential identification of variants specific to a more restricted MDD phenotype. A balanced portfolio reconciling both study design approaches is the optimal approach to progress further in unraveling the genetic architecture of depression.

Genetic influences on eight psychiatric disorders based on family data of 4 408 646 full and half-siblings, and genetic data of 333 748 cases and controls.

BACKGROUND: Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders. METHODS: We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia. RESULTS: Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50. CONCLUSIONS: Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

Adverse life events, psychiatric history, and biological predictors of postpartum depression in an ethnically diverse sample of postpartum women.

BACKGROUND: Race, psychiatric history, and adverse life events have all been independently associated with postpartum depression (PPD). However, the role these play together in Black and Latina women remains inadequately studied. Therefore, we performed a case-control study of PPD, including comprehensive assessments of symptoms and biomarkers, while examining the effects of genetic ancestry. METHODS: We recruited our sample (549 cases, 968 controls) at 6 weeks postpartum from obstetrical clinics in North Carolina. PPD status was determined using the MINI-plus. Psychiatric history was extracted from medical records. Participants were administered self-report instruments to assess depression (Edinburgh Postnatal Depression Scale) and adverse life events. Levels of estradiol, progesterone, brain-derived neurotrophic factor, oxytocin, and allopregnanalone were assayed. Principal components from genotype data were used to estimate genetic ancestry and logistic regression was used to identify predictors of PPD. RESULTS: This population was racially diverse (68% Black, 13% Latina, 18% European). Genetic ancestry was not a predictor of PPD. Case status was predicted by a history of major depression (p = 4.01E-14), lifetime anxiety disorder diagnosis (p = 1.25E-34), and adverse life events (p = 6.06E-06). There were no significant differences between groups in any hormones or neurosteroids. CONCLUSIONS: Psychiatric history and multiple exposures to adverse life events were significant predictors of PPD in a population of minority and low-income women. Genetic ancestry and hormone levels were not predictive of case status. Increased genetic vulnerability in conjunction with risk factors may predict the onset of PPD, whereas genetic ancestry does not appear predictive.

Genetic risk scores and family history as predictors of schizophrenia in Nordic registers.

BACKGROUND: Family history is a long-standing and readily obtainable risk factor for schizophrenia (SCZ). Low-cost genotyping technologies have enabled large genetic studies of SCZ, and the results suggest the utility of genetic risk scores (GRS, direct assessments of inherited common variant risk). Few studies have evaluated family history and GRS simultaneously to ask whether one can explain away the other. METHODS: We studied 5959 SCZ cases and 8717 controls from four Nordic countries. All subjects had family history data from national registers and genome-wide genotypes that were processed through the quality control procedures used by the Psychiatric Genomics Consortium. Using external training data, GRS were estimated for SCZ, bipolar disorder (BIP), major depression, autism, educational attainment, and body mass index. Multivariable modeling was used to estimate effect sizes. RESULTS: Using harmonized genomic and national register data from Denmark, Estonia, Norway, and Sweden, we confirmed that family history of SCZ and GRS for SCZ and BIP were risk factors for SCZ. In a joint model, the effects of GRS for SCZ and BIP were essentially unchanged, and the effect of family history was attenuated but remained significant. The predictive capacity of a model including GRS and family history neared the minimum for clinical utility. CONCLUSIONS: Combining national register data with measured genetic risk factors represents an important investigative approach for psychotic disorders. Our findings suggest the potential clinical utility of combining GRS and family history for early prediction and diagnostic improvements.

Improved ethical guidance for the return of results from psychiatric genomics research.

There is an emerging consensus that genomic researchers should, at a minimum, offer to return to individual participants clinically valid, medically important and medically actionable genomic findings (for example, pathogenic variants in BRCA1) identified in the course of research. However, this is not a common practice in psychiatric genetics research. Furthermore, psychiatry researchers often generate findings that do not meet all of these criteria, yet there may be ethically compelling arguments to offer selected results. Here, we review the return of results debate in genomics research and propose that, as for genomic studies of other medical conditions, psychiatric genomics researchers should offer findings that meet the minimum criteria stated above. Additionally, if resources allow, psychiatry researchers could consider offering to return pre-specified 'clinically valuable' findings even if not medically actionable-for instance, findings that help corroborate a psychiatric diagnosis, and findings that indicate important health risks. Similarly, we propose offering 'likely clinically valuable' findings, specifically, variants of uncertain significance potentially related to a participant's symptoms. The goal of this Perspective is to initiate a discussion that can help identify optimal ways of managing the return of results from psychiatric genomics research.

Adverse life events increase risk for postpartum psychiatric episodes: A population-based epidemiologic study.

BACKGROUND: Trauma histories may increase risk of perinatal psychiatric episodes. We designed an epidemiological population-based cohort study to explore if adverse childhood experiences (ACE) in girls increases risk of later postpartum psychiatric episodes. METHODS: Using Danish registers, we identified women born in Denmark between January 1980 and December 1998 (129,439 childbirths). Exposure variables were ACE between ages 0 and 15 including: (1) family disruption, (2) parental somatic illness, (3) parental labor market exclusion, (4) parental criminality, (5) parental death, (6) placement in out-of-home care, (7) parental psychopathology excluding substance use, and (8) parental substance use disorder. Primary outcome was first occurrence of in- or outpatient contact 0-6 months postpartum at a psychiatric treatment facility with any psychiatric diagnoses, ICD-10, F00-F99 (N = 651). We conducted survival analyses using Cox proportional hazard regressions of postpartum psychiatric episodes. RESULTS: Approximately 52% of the sample experienced ACE, significantly increasing risk of any postpartum psychiatric diagnosis. Highest risks were observed among women who experienced out-of-home placement, hazard ratio (HR) 2.57 (95% CI: 1.90-3.48). Women experiencing two adverse life events had higher risks of postpartum psychiatric diagnosis HR: 1.88 (95% CI: 1.51-2.36), compared to those with one ACE, HR: 1.24 (95% CI: 1.03-49) and no ACE, HR: 1.00 (reference group). CONCLUSIONS: ACE primarily due to parental psychopathology and disability contributes to increased risk of postpartum psychiatric episodes; and greater numbers of ACE increases risk for postpartum psychiatric illness with an observed dose-response effect. Future work should explore genetic and environmental factors that increase risk and/or confer resilience.

Comparative genomic evidence for the involvement of schizophrenia risk genes in antipsychotic effects.

Genome-wide association studies (GWAS) for schizophrenia have identified over 100 loci encoding >500 genes. It is unclear whether any of these genes, other than dopamine receptor D2, are immediately relevant to antipsychotic effects or represent novel antipsychotic targets. We applied an in vivo molecular approach to this question by performing RNA sequencing of brain tissue from mice chronically treated with the antipsychotic haloperidol or vehicle. We observed significant enrichments of haloperidol-regulated genes in schizophrenia GWAS loci and in schizophrenia-associated biological pathways. Our findings provide empirical support for overlap between genetic variation underlying the pathophysiology of schizophrenia and the molecular effects of a prototypical antipsychotic.

Genome-wide association analysis identifies common variants influencing infant brain volumes.

Genome-wide association studies (GWAS) of adolescents and adults are transforming our understanding of how genetic variants impact brain structure and psychiatric risk, but cannot address the reality that psychiatric disorders are unfolding developmental processes with origins in fetal life. To investigate how genetic variation impacts prenatal brain development, we conducted a GWAS of global brain tissue volumes in 561 infants. An intronic single-nucleotide polymorphism (SNP) in IGFBP7 (rs114518130) achieved genome-wide significance for gray matter volume (P=4.15 × 10-10). An intronic SNP in WWOX (rs10514437) neared genome-wide significance for white matter volume (P=1.56 × 10-8). Additional loci with small P-values included psychiatric GWAS associations and transcription factors expressed in developing brain. Genetic predisposition scores for schizophrenia and ASD, and the number of genes impacted by rare copy number variants (CNV burden) did not predict global brain tissue volumes. Integration of these results with large-scale neuroimaging GWAS in adolescents (PNC) and adults (ENIGMA2) suggests minimal overlap between common variants impacting brain volumes at different ages. Ultimately, by identifying genes contributing to adverse developmental phenotypes, it may be possible to adjust adverse trajectories, preventing or ameliorating psychiatric and developmental disorders.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10-8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effect.

The impact of education, country, race and ethnicity on the self-report of postpartum depression using the Edinburgh Postnatal Depression Scale.

BACKGROUND: Universal screening for postpartum depression is recommended in many countries. Knowledge of whether the disclosure of depressive symptoms in the postpartum period differs across cultures could improve detection and provide new insights into the pathogenesis. Moreover, it is a necessary step to evaluate the universal use of screening instruments in research and clinical practice. In the current study we sought to assess whether the Edinburgh Postnatal Depression Scale (EPDS), the most widely used screening tool for postpartum depression, measures the same underlying construct across cultural groups in a large international dataset. METHOD: Ordinal regression and measurement invariance were used to explore the association between culture, operationalized as education, ethnicity/race and continent, and endorsement of depressive symptoms using the EPDS on 8209 new mothers from Europe and the USA. RESULTS: Education, but not ethnicity/race, influenced the reporting of postpartum depression [difference between robust comparative fit indexes (∆*CFI) 0.01), but not between European countries (∆*CFI < 0.01). CONCLUSIONS: Investigators and clinicians should be aware of the potential differences in expression of phenotype of postpartum depression that women of different educational backgrounds may manifest. The increasing cultural heterogeneity of societies together with the tendency towards globalization requires a culturally sensitive approach to patients, research and policies, that takes into account, beyond rhetoric, the context of a person's experiences and the context in which the research is conducted.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

Modeling psychiatric disorders: from genomic findings to cellular phenotypes.

Major programs in psychiatric genetics have identified >150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes.

A genome-wide association study of kynurenic acid in cerebrospinal fluid: implications for psychosis and cognitive impairment in bipolar disorder.

Elevated cerebrospinal fluid (CSF) levels of the glia-derived N-methyl-D-aspartic acid receptor antagonist kynurenic acid (KYNA) have consistently been implicated in schizophrenia and bipolar disorder. Here, we conducted a genome-wide association study based on CSF KYNA in bipolar disorder and found support for an association with a common variant within 1p21.3. After replication in an independent cohort, we linked this genetic variant-associated with reduced SNX7 expression-to positive psychotic symptoms and executive function deficits in bipolar disorder. A series of post-mortem brain tissue and in vitro experiments suggested SNX7 downregulation to result in a caspase-8-driven activation of interleukin-1ß and a subsequent induction of the brain kynurenine pathway. The current study demonstrates the potential of using biomarkers in genetic studies of psychiatric disorders, and may help to identify novel drug targets in bipolar disorder.