Modern Views of Machine Learning for Precision Psychiatry

In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of precision psychiatry. Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment. Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health. In this review, we provide a comprehensive review of the ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice. Additionally, we review the role of ML in molecular phenotyping and cross-species biomarker identification in precision psychiatry. We further discuss explainable AI (XAI) and causality testing in a closed-human-in-the-loop manner, and highlight the ML potential in multimedia information extraction and multimodal data fusion. Finally, we discuss conceptual and practical challenges in precision psychiatry and highlight ML opportunities in future research

CDG: an online server proposing biologically closest disease-causing genes and pathologies and its application to primary immunodeficiency

Summary: In analyses of exome data, candidate gene selection can be challenging in the absence of variants in known disease-causing genes. We calculated the putative biologically closest known disease-causing genes for 13,005 human genes not currently reported to be disease-causing. We used these data to construct the Closest Disease-Causing Genes (CDG) server, which can be used to infer the closest associated disease-causing genes and phenotypes for lists of candidate genes. This resource will be a considerable asset for ascertaining the poten-tial relevance of lists of genes to specific diseases of interest

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

Human IFN-γ immunity to mycobacteria is governed by both IL-12 and IL-23

Hundreds of patients with autosomal recessive, complete IL-12p40 or IL-12Rß1 deficiency have been diagnosed over the last 20 years. They typically suffer from invasive mycobacteriosis and, occasionally, from mucocutaneous candidiasis. Susceptibility to these infections is thought to be due to impairments of IL- 12–dependent IFN-? immunity and IL-23–dependent IL-17A/IL-17F immunity, respectively. We report here patients with autosomal recessive, complete IL- 12Rß2 or IL-23R deficiency, lacking responses to IL-12 or IL- 23 only, all of whom, unexpectedly, display mycobacteriosis without candidiasis. We show that aß T, ?d T, B, NK, ILC1, and ILC2 cells from healthy donors preferentially produce IFN-? in response to IL-12, whereas NKT cells and MAIT cells preferentially produce IFN-? in response to IL-23. We also show that the development of IFN-?–producing CD4+ T cells, including, in particular, mycobacterium-specific TH1* cells (CD45RA-CCR6+), is dependent on both IL-12 and IL-23. Last, we show that IL12RB1, IL12RB2, and IL23R have similar frequencies of deleterious variants in the general population. The comparative rarity of symptomatic patients with IL-12Rß2 or IL-23R deficiency, relative to IL-12Rß1 deficiency, is, therefore, due to lower clinical penetrance. There are fewer symptomatic IL-23R– and IL-12Rß2–deficient than IL-12Rß1–deficient patients, not because these genetic disorders are rarer, but because the isolated absence of IL-12 or IL-23 is, in part, compensated by the other cytokine for the production of IFN-?, thereby providing some protection against mycobacteria. These experiments of nature show that human IL-12 and IL-23 are both required for optimal IFN-?–dependent immunity to mycobacteria, both individually and much more so cooperatively

A novel Alzheimer disease locus located near the gene encoding tau protein

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordAPOE ε4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ε4+ (10 352 cases and 9207 controls) and APOE ε4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ε4 status. Suggestive associations (P<1 × 10-4) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ε4+: 1250 cases and 536 controls; APOE ε4-: 718 cases and 1699 controls). Among APOE ε4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10-9). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ε4+ subjects (CR1 and CLU) or APOE ε4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10-7) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P≤1.3 × 10-8), frontal cortex (P≤1.3 × 10-9) and temporal cortex (P≤1.2 × 10-11). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10-6) and temporal cortex (P=2.6 × 10-6). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ε4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted

Intérêt de l'équilibre de Hardy-Weinberg et détection des délétions chromosomiques dans les données de séquençage d’exome à partir de grands ensembles de données

Un des principaux centres d'intérêt de la génétique humaine est l'identification des variants qui peuvent contribuer aux maladies humaines ou aux traits adaptatifs. Les approches de séquençage de nouvelle génération (NGS), y compris le séquençage de l'exome entier (WES), offrent des opportunités sans précédent pour découvrir de nouveaux variants impliqués dans la sensibilité ou la résistance à une pathologie. Le principe de base du WES est le séquençage des régions codantes, grâce auquel des sondes ADN sont utilisées pour s'hybrider avec la partie codante du génome. Après le séquençage, des millions de séquences d'ADN, appelées reads, sont alignées sur un génome de référence et sont analysées par différents outils, avec l'objectif d'identifier de nouvelles cibles pertinentes pour la question scientifique posée. Depuis leur création, les méthodes NGS, y compris le WES, ont fourni une énorme quantité de données qui posent des défis considérables pour leur analyse et l'interprétation des résultats correspondants. Ces avancées technologiques nécessitent de plus en plus le développement d'approches méthodologiques sophistiquées, générant ainsi de nouvelles questions de recherche afin d'optimiser l’analyse de ces données. Ainsi, les volumes de données d'exome accumulées au fil des ans permet de poser des questions scientifiques nouvelles. Ma thèse a porté sur ces aspects. Tout d'abord, j'ai développé une approche qui permet de filtrer les variants qui sont des faux positifs et qui n’étaient pas éliminés avec les approches bioinformatiques classiques. Nous avons regroupé ces variants dans une « blacklist » et les avons caractérisés in silico et de façon expérimentale. Nous avons en particulier montré qu'un sous-ensemble de ces variants ne respectaient pas l'équilibre de Hardy-Weinberg (HW), un principe fondamental de génétique des populations généralement utilisé comme critère de filtre dans les études de génotypage à grande échelle ( par exemple les études d’association génome entier). Sur la base de ces résultats initiaux, nous avons débuté une étude plus systématique de l'équilibre HW à plus grande échelle pour déterminer si ce test pourrait être utilisé non seulement pour détecter des erreurs techniques, mais aussi pour informer sur des phénomènes importants et pertinents en termes de génétique des populations. Nos données préliminaires se concentrant sur les variants avec un excès ou une perte d'homozygotes pour l'allèle mineur ont révélé certains variants candidats prometteurs qui pourraient indiquer un effet protecteur (dans FUT2, et SMN2) ou désavantageux (dans FANCD2) vis-à-vis ce certaines pathologies. Au cours de cette thèse, j'ai également abordé la question de la détection des variations du nombre de copies (CNV) dans les données WES. Les CNV sont une classe spécifique de variants traditionnellement difficiles à détecter dans les données d'exome de cohortes de laboratoire qui sont générées au fil du temps. Dans ma thèse, j'ai développé HMZDelFinder-opt, un algorithme qui permet d’optimiser la détection de délétions homozygotes et hémizygotes et d'identifier des délétions partielles d'exons. En utilisant HMZDelFinder_opt avec à la fois des délétions pathogènes validées et des données simulées, nous avons démontré que la sélection optimisée d'un ensemble d’exomes contrôles de référence avec un profil de couverture similaire à celui de l'échantillon WES étudié réduisait le nombre de délétions faussement détectées, tout en améliorant l’identification des véritables délétions homozygotes. HMZDelFinder_opt permet également de fournir un nouvel outil pour l'identification systématique des délétions partielles d'exon. Au total, les questions traités dans ma thèse ont permis de proposer des approches nouvelles afin d’améliorer l’identification de nouveaux déterminants génétiques de pathologies humaines.A major focus of human genetics is on the identification of variants that may contribute to human diseases or adaptive traits. Next-generation sequencing (NGS) approaches, including whole exome sequencing (WES), provide unprecedent opportunities for discovering novel variants that may underlie susceptibility or resistance to disease. The basic principle of WES is the sequencing of coding regions, whereby DNA probes or baits are used to hybridize with the protein-coding portion of the genome, isolating it from the non-coding portions. After sequencing, millions of DNA sequences, known as reads, are aligned to a reference genome and undergo many types of downstream analysis, whereby the common goal is to identify novel targets underlying the scientific question that is being asked. Since its inception, NGS methods, including WES, have been providing an enormous amount of data at sustainable costs but also posing considerable challenges for the analysis and interpretation of the results. These technological advances increasingly require the development of sophisticated computational approaches, thus generating new research avenues in order to appropriately analyze and interpret enormous amounts of data. In turn, the wealth of exome data accumulated over the years has given the opportunity to pose scientific questions in ways that could not be possible earlier. My thesis took advantage from both these aspects. First, I developed a computational approach that allows filtering of false positive variants that cannot be discarded with traditional bioinformatic approaches. We collectively referred to these variants as ‘blacklist’ and characterized them computationally and experimentally, discovering that a subset is out of Hardy-Weinberg (HW) equilibrium, a fundamental population genetic principle typically used as a filtering criterion in large-scale genotyping studies (e.g. GWAS). Based on these initial findings, we are currently studying HW equilibrium systematically and at a larger scale to determine whether HW equilibrium could be used not only to detect technical errors but also to inform about important phenomena relevant to population genetics. Our preliminary data focusing on variants with an excess or loss of homozygotes for the minor allele revealed promising candidate variants that could be indicative of protection (eg in FUT2, SMN2) or disadvantage (eg in FANCD2) to disease. Second, I tackled the question of detection of copy number variants (CNVs) in WES data. CNVs are a specific class of variants traditionally difficult to detect in exome data of typical laboratory cohorts that are generated over time. In my thesis, I developed HMZDelFinder-opt, an algorithm that allows identification of partial exon homozygous and hemizygous deletions. Using HMZDelFinder_opt with both validated disease-causing deletions and simulated data, we demonstrated that the a priori selection of a reference control set with a coverage profile similar to that of the WES sample studied reduced the number of deletions detected, while improving the ranking of the true homozygous deletion. HMZDelFinder_opt also fills the gap in the study of deletions spanning less than an exon, by providing the first tool for the systematic identification of partial exon deletions. Collectively, these projects tackle heretofore-unexamined topics and hold promise to discover novel causal determinants of human diseases or traits

Intérêt de l'équilibre de Hardy-Weinberg et détection des délétions chromosomiques dans les données de séquençage d’exome à partir de grands ensembles de données

A major focus of human genetics is on the identification of variants that may contribute to human diseases or adaptive traits. Next-generation sequencing (NGS) approaches, including whole exome sequencing (WES), provide unprecedent opportunities for discovering novel variants that may underlie susceptibility or resistance to disease. The basic principle of WES is the sequencing of coding regions, whereby DNA probes or baits are used to hybridize with the protein-coding portion of the genome, isolating it from the non-coding portions. After sequencing, millions of DNA sequences, known as reads, are aligned to a reference genome and undergo many types of downstream analysis, whereby the common goal is to identify novel targets underlying the scientific question that is being asked. Since its inception, NGS methods, including WES, have been providing an enormous amount of data at sustainable costs but also posing considerable challenges for the analysis and interpretation of the results. These technological advances increasingly require the development of sophisticated computational approaches, thus generating new research avenues in order to appropriately analyze and interpret enormous amounts of data. In turn, the wealth of exome data accumulated over the years has given the opportunity to pose scientific questions in ways that could not be possible earlier. My thesis took advantage from both these aspects. First, I developed a computational approach that allows filtering of false positive variants that cannot be discarded with traditional bioinformatic approaches. We collectively referred to these variants as ‘blacklist’ and characterized them computationally and experimentally, discovering that a subset is out of Hardy-Weinberg (HW) equilibrium, a fundamental population genetic principle typically used as a filtering criterion in large-scale genotyping studies (e.g. GWAS). Based on these initial findings, we are currently studying HW equilibrium systematically and at a larger scale to determine whether HW equilibrium could be used not only to detect technical errors but also to inform about important phenomena relevant to population genetics. Our preliminary data focusing on variants with an excess or loss of homozygotes for the minor allele revealed promising candidate variants that could be indicative of protection (eg in FUT2, SMN2) or disadvantage (eg in FANCD2) to disease. Second, I tackled the question of detection of copy number variants (CNVs) in WES data. CNVs are a specific class of variants traditionally difficult to detect in exome data of typical laboratory cohorts that are generated over time. In my thesis, I developed HMZDelFinder-opt, an algorithm that allows identification of partial exon homozygous and hemizygous deletions. Using HMZDelFinder_opt with both validated disease-causing deletions and simulated data, we demonstrated that the a priori selection of a reference control set with a coverage profile similar to that of the WES sample studied reduced the number of deletions detected, while improving the ranking of the true homozygous deletion. HMZDelFinder_opt also fills the gap in the study of deletions spanning less than an exon, by providing the first tool for the systematic identification of partial exon deletions. Collectively, these projects tackle heretofore-unexamined topics and hold promise to discover novel causal determinants of human diseases or traits.Un des principaux centres d'intérêt de la génétique humaine est l'identification des variants qui peuvent contribuer aux maladies humaines ou aux traits adaptatifs. Les approches de séquençage de nouvelle génération (NGS), y compris le séquençage de l'exome entier (WES), offrent des opportunités sans précédent pour découvrir de nouveaux variants impliqués dans la sensibilité ou la résistance à une pathologie. Le principe de base du WES est le séquençage des régions codantes, grâce auquel des sondes ADN sont utilisées pour s'hybrider avec la partie codante du génome. Après le séquençage, des millions de séquences d'ADN, appelées reads, sont alignées sur un génome de référence et sont analysées par différents outils, avec l'objectif d'identifier de nouvelles cibles pertinentes pour la question scientifique posée. Depuis leur création, les méthodes NGS, y compris le WES, ont fourni une énorme quantité de données qui posent des défis considérables pour leur analyse et l'interprétation des résultats correspondants. Ces avancées technologiques nécessitent de plus en plus le développement d'approches méthodologiques sophistiquées, générant ainsi de nouvelles questions de recherche afin d'optimiser l’analyse de ces données. Ainsi, les volumes de données d'exome accumulées au fil des ans permet de poser des questions scientifiques nouvelles. Ma thèse a porté sur ces aspects. Tout d'abord, j'ai développé une approche qui permet de filtrer les variants qui sont des faux positifs et qui n’étaient pas éliminés avec les approches bioinformatiques classiques. Nous avons regroupé ces variants dans une « blacklist » et les avons caractérisés in silico et de façon expérimentale. Nous avons en particulier montré qu'un sous-ensemble de ces variants ne respectaient pas l'équilibre de Hardy-Weinberg (HW), un principe fondamental de génétique des populations généralement utilisé comme critère de filtre dans les études de génotypage à grande échelle ( par exemple les études d’association génome entier). Sur la base de ces résultats initiaux, nous avons débuté une étude plus systématique de l'équilibre HW à plus grande échelle pour déterminer si ce test pourrait être utilisé non seulement pour détecter des erreurs techniques, mais aussi pour informer sur des phénomènes importants et pertinents en termes de génétique des populations. Nos données préliminaires se concentrant sur les variants avec un excès ou une perte d'homozygotes pour l'allèle mineur ont révélé certains variants candidats prometteurs qui pourraient indiquer un effet protecteur (dans FUT2, et SMN2) ou désavantageux (dans FANCD2) vis-à-vis ce certaines pathologies. Au cours de cette thèse, j'ai également abordé la question de la détection des variations du nombre de copies (CNV) dans les données WES. Les CNV sont une classe spécifique de variants traditionnellement difficiles à détecter dans les données d'exome de cohortes de laboratoire qui sont générées au fil du temps. Dans ma thèse, j'ai développé HMZDelFinder-opt, un algorithme qui permet d’optimiser la détection de délétions homozygotes et hémizygotes et d'identifier des délétions partielles d'exons. En utilisant HMZDelFinder_opt avec à la fois des délétions pathogènes validées et des données simulées, nous avons démontré que la sélection optimisée d'un ensemble d’exomes contrôles de référence avec un profil de couverture similaire à celui de l'échantillon WES étudié réduisait le nombre de délétions faussement détectées, tout en améliorant l’identification des véritables délétions homozygotes. HMZDelFinder_opt permet également de fournir un nouvel outil pour l'identification systématique des délétions partielles d'exon. Au total, les questions traités dans ma thèse ont permis de proposer des approches nouvelles afin d’améliorer l’identification de nouveaux déterminants génétiques de pathologies humaines

Effects of Stress Throughout the Lifespan on the Brain and Behavior

Why do some individuals succumb to stress and develop debilitating psychiatric deseases including depression and posttraumatic disorders, whereas others adapt well in the face of adverse events? Resilience is the ability to cope with, learn from, and thrive in the face of adversity. Resilience is built over the life course, beginning early in life, and is based on the remarkable plasticity of the developing and adult brains to a continuously changing environment. Understanding the neural bases of individual and sex differences in responses to stress on brain development and functions is essential to the development of better pharmaceuticals to either promote coping mechanisms (preventive care) or mitigate maladaptive stress responses (curative care). After describing the new view of epigenetics that adds to the old notion that “biology is destiny,” this chapter summarizes some of the underlying mechanisms of stress effects upon the brain and the body and provides a perspective on the emerging contribution of high-throughput technologies and next-generation interventions to develop and enhance resilienc