Publications by authors named "Carlos N Pato"

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study).

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Article Synopsis
  • - The PUMAS project aims to address the lack of representation of African and Latin American populations in psychiatric genetics studies by analyzing genetic data from individuals with serious mental illness (SMI), including disorders like schizophrenia and bipolar disorder, using data from 89,320 participants across four different cohorts.
  • - The research involves harmonizing data from various clinical assessments to create standardized measures of mental health symptoms, which allows for more accurate genetic analyses across different diagnoses and symptoms.
  • - The findings show that schizophrenia and severe bipolar disorder are the most common diagnoses among participants, and a set of 19 key symptoms has been identified, which may be useful for cross-diagnosis genetic studies.
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We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations.

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Translating genetic findings for neurodevelopmental and psychiatric disorders (NPDs) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop codons (iSTOP) that lead to mRNA nonsense-mediated decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 genes.

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Large-scale genome-wide association studies of schizophrenia have uncovered hundreds of associated loci but with extremely limited representation of African diaspora populations. We surveyed electronic health records of 200,000 individuals of African ancestry in the Million Veteran and All of Us Research Programs, and, coupled with genotype-level data from four case-control studies, realized a combined sample size of 13,012 affected and 54,266 unaffected persons. Three genome-wide significant signals - near , , and - are the first to be independently identified in populations of predominantly African ancestry.

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Translating genetic findings for neurodevelopmental and psychiatric disorders (NPD) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, here we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop-codons (iSTOP) that lead to mRNA nonsense-mediated-decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 NPD genes.

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Article Synopsis
  • Accurately diagnosing bipolar disorder (BD) can take around 7 years due to its overlap with unipolar major depressive disorder (MDD), especially since the first manic episode often follows a depressive one.
  • This study uses genome-wide association analyses (GWAS) and polygenic risk scores (PRS) from a large cohort to identify genetic factors that could help differentiate between BD and MDD early on.
  • The results show that while BD and MDD are genetically distinct and share a continuum of genetic risk, larger future studies are needed to enhance the accuracy of these genetic predictors for early diagnosis.
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Motivation: Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted.

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The study of neurodevelopmental molecular mechanisms in schizophrenia requires the development of adequate biological models such as patient-derived cells and their derivatives. We previously utilized cell lines with neural progenitor properties (CNON) derived from the superior or middle turbinates of patients with schizophrenia and control groups to study schizophrenia-specific gene expression. In this study, we analyzed single-cell RNA seq data from two CNON cell lines (one derived from an individual with schizophrenia (SCZ) and the other from a control group) and two biopsy samples from the middle turbinate (MT) (also from an individual with SCZ and a control).

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We examined the presence of adverse events in both childhood and adulthood and the prevalence of PTSD in individuals with Bipolar Disorder (BD). There were 191 adults diagnosed with BD Type I and 924 controls, of predominantly African Ancestry (AA). All were administered the GPC-Screening Tool and the BD group the DIPAD.

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Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes. This recent study-and most other large-scale human genetics studies-was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear.

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Obsessive-compulsive disorder (OCD) is a complex, multifactorial disorder with onset in either childhood or early adulthood. Lifetime prevalence has been estimated to be around 2%-3%. groups OCD together with closely related disorders-body dysmorphic disorder, trichotillomania (hair-pulling disorder), hoarding disorder, and excoriation disorder (skin-picking disorder)-as obsessive-compulsive and related disorders (OCRDs).

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Bipolar disorder (BD) is a clinically heterogeneous condition, presenting a complex underlying etiopathogenesis that is not sufficiently characterized. Without molecular biomarkers being used in the clinical environment, several large screen proteomics studies have been conducted to provide valuable molecular information. Mass spectrometry (MS)-based techniques can be a powerful tool for the identification of disease biomarkers, improving prediction and diagnosis ability.

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Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183).

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Article Synopsis
  • * Researchers discovered 287 genomic regions associated with schizophrenia, emphasizing genes specifically active in excitatory and inhibitory neurons, and identified 120 key genes potentially responsible for these associations.
  • * The findings highlight important biological processes related to neuronal function, suggesting overlaps between common and rare genetic variants in both schizophrenia and neurodevelopmental disorders, ultimately aiding future research on these conditions.
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  • A meta-analysis of whole exomes from 24,248 schizophrenia cases and 97,322 controls identified ultra-rare coding variants (URVs) linked to schizophrenia risk across 10 significant genes.
  • Some of these genes are heavily expressed in the brain and are involved in synapse formation, pointing to a connection between glutamate system dysfunction and schizophrenia.
  • Additionally, there's an overlap in rare variant risks shared with other disorders like autism and epilepsy, suggesting that both common and rare genetic factors contribute to the same biological processes underlying schizophrenia.
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Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown.

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Polygenic risk scores (PRS) summarize genetic liability to a disease at the individual level, and the aim is to use them as biomarkers of disease and poor outcomes in real-world clinical practice. To date, few studies have assessed the prognostic value of PRS relative to standards of care. Schizophrenia (SCZ), the archetypal psychotic illness, is an ideal test case for this because the predictive power of the SCZ PRS exceeds that of most other common diseases.

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Background: Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

Methods: We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

Results: We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects.

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This scoping review of population-based epidemiological studies was done to provide background information on the prevalences and distribution of psychiatric disorders in Africa for calls to broaden diversity in psychiatric genetic studies. We searched PubMed, EMBASE, and Web of Science to retrieve relevant literature in English, French, and Portuguese from Jan 1, 1984, to Aug 18, 2020. In 36 studies from 12 African countries, the lifetime prevalence ranged from 3·3% to 9·8% for mood disorders, from 5·7% to 15·8% for anxiety disorders, from 3·7% to 13·3% for substance use disorders, and from 1·0% to 4·4% for psychotic disorders.

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Background: Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world's population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572.

Methods: We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings.

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Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this research, we show that Asparouhov and Muthén's alignment method can be adapted to align data from disparate item sets and response formats.

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Many common illnesses, for reasons that have not been identified, differentially affect men and women. For instance, the autoimmune diseases systemic lupus erythematosus (SLE) and Sjögren's syndrome affect nine times more women than men, whereas schizophrenia affects men with greater frequency and severity relative to women. All three illnesses have their strongest common genetic associations in the major histocompatibility complex (MHC) locus, an association that in SLE and Sjögren's syndrome has long been thought to arise from alleles of the human leukocyte antigen (HLA) genes at that locus.

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Background: Genome-wide association studies of schizophrenia have demonstrated that variations in noncoding regions are responsible for most of the common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Therefore, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease.

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Detecting and estimating DNA sample contamination are important steps to ensure high-quality genotype calls and reliable downstream analysis. Existing methods rely on population allele frequency information for accurate estimation of contamination rates. Correctly specifying population allele frequencies for each individual in early stage of sequence analysis is impractical or even impossible for large-scale sequencing centers that simultaneously process samples from multiple studies across diverse populations.

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