Assessing structural models of neighborhood and family sociodemographic characteristics and their relations with externalizing psychopathology.

Externalizing psychopathology has been found to have small to moderate associations with neighborhood and family sociodemographic characteristics. However, prior studies may have used suboptimal operationalizations of neighborhood sociodemographic characteristics and externalizing psychopathology, potentially misestimating relations between these constructs. To address these limitations, in the current study we test different measurement models of these constructs and assess the structural relations between them. Using a population-representative sample of 2,195 twins and siblings from the Georgia Twin Study and data from the National Neighborhood Data Archive and 2000 U.S. Census, we assessed the fit of competing measurement models for family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics. In structural models, we regressed a general externalizing dimension on different operationalizations of these variables separately and then simultaneously in a final model. Latent variable operationalizations of family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics explained no more variance in broad externalizing psychopathology than other operationalizations. In an omnibus model, family sociodemographic characteristics showed a small association with externalizing psychopathology, while neighborhood sociodemographic and environmental characteristics did not. Family sociodemographic characteristics showed small associations with neighborhood sociodemographic and environmental characteristics, and neighborhood sociodemographic characteristics were moderately associated with neighborhood environment. These findings suggest that family sociodemographic characteristics are more associated with the development of broad externalizing psychopathology in youth than neighborhood sociodemographic characteristics and neighborhood environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Principles and procedures for revising the hierarchical taxonomy of psychopathology.

Quantitative, empirical approaches to establishing the structure of psychopathology hold promise to improve on traditional psychiatric classification systems. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a framework that summarizes the substantial and growing body of quantitative evidence on the structure of psychopathology. To achieve its aims, HiTOP must incorporate emerging research in a systematic, ongoing fashion. In this article, we describe the historical context and grounding of the principles and procedures for revising the HiTOP framework. Informed by strengths and shortcomings of previous classification systems, the proposed revisions protocol is a formalized system focused around three pillars: (a) prioritizing systematic evaluation of quantitative evidence by a set of transparent criteria and processes, (b) balancing stability with flexibility, and (c) promoting inclusion over gatekeeping in all aspects of the process. We detail how the revisions protocol will be applied in practice, including the scientific and administrative aspects of the process. Additionally, we describe areas of the HiTOP structure that will be a focus of early revisions and outline challenges for the revisions protocol moving forward. The proposed revisions protocol is designed to ensure that the HiTOP framework reflects the current state of scientific knowledge on the structure of psychopathology and fulfils its potential to advance clinical research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating alternative models of youth externalizing using quantitative genetic analyses.

Interest has increased in the recent literature on characterizing psychopathology dimensionally in hierarchical models. One dimension of psychopathology that has received considerable attention is externalizing. Although extensively studied and well-characterized in late adolescents and adults, delineation of the externalizing spectrum in youth has lagged behind. As a complement to structural analyses of externalizing, in this study, we use quantitative genetic analyses of twin data to adjudicate among alternative models of youth externalizing that differ in granularity. Specifically, we compared model fit, estimates of genetic and environmental influences on the externalizing dimension, and the average, variability, and precision of genetic and environmental influences on individual symptoms due to the externalizing dimension, specific symptom dimensions, and unique etiological influences. Given that none of these criteria are definitive on their own, we looked to the confluence of these criteria to exclude particular models while highlighting others as leading contenders. We analyzed parent-report data on 38 externalizing symptoms from a population-representative, ethnically diverse sample of 883 youth twin pairs (51% female), who were on average 8.5 years old. Although models including an externalizing composite and attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder diagnoses and symptom dimensions showed similar heritability to latent variable models of externalizing, models that included latent dimensions of externalizing and more fine-grained symptom dimensions fit better and were more balanced in the magnitude of genetic and environmental influences on individual symptoms due to the externalizing dimension and specific symptom dimensions. Pending replication, these more granular and elaborated model(s) can be useful for advancing research on causes and outcomes of youth externalizing and its fine-grained specific components. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics.

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, although down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci; the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses were found robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who generate and share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.

A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders.

Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (rg s ≥ 0.87), and between the effect sizes of genetic correlations with external traits (rg  ≥ 0.95). Nevertheless, 21 of the 84 correlations with external criteria showed small, significant differences between externalizing and addiction risk factors. MiXer results showed that approximately 81% of influential externalizing variants were shared with addiction risk, whereas addiction risk shared 56% of its influential variants with externalizing. These results suggest that externalizing and addiction genetic risk are largely shared, though both constructs also retain meaningful unshared genetic variance. These results can inform future efforts to identify specific genetic influences on externalizing and SUDs.

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies.

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

Differentiation latency and dormancy signatures define fetal liver HSCs at single cell resolution.

Decoding the gene regulatory mechanisms mediating self-renewal of hematopoietic stem cells (HSCs) during their amplification in the fetal liver (FL) is relevant for advancing therapeutic applications aiming to expand transplantable HSCs, a long-standing challenge. Here, to explore intrinsic and extrinsic regulation of self-renewal in FL-HSCs at the single cell level, we engineered a culture platform designed to recapitulate the FL endothelial niche, which supports the amplification of serially engraftable HSCs ex vivo. Leveraging this platform in combination with single cell index flow cytometry, serial transplantation assays, and single cell RNA-sequencing, we elucidated previously unrecognized heterogeneity in immunophenotypically defined FL-HSCs and demonstrated that differentiation latency and transcriptional signatures of biosynthetic dormancy are distinguishing properties of self-renewing FL-HSCs with capacity for serial, long-term multilineage hematopoietic reconstitution. Altogether, our findings provide key insights into HSC expansion and generate a novel resource for future exploration of the intrinsic and niche-derived signaling pathways that support FL-HSC self-renewal.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics.

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.

A broad internalizing dimension accounts for the genetic associations between personality and individual internalizing disorders.

Much research has demonstrated that psychopathology can be described in terms of broad dimensions, representing liability for multiple psychiatric disorders. Broad spectra of psychopathology (e.g., internalizing and externalizing) are increasingly used as targets for research investigating the development, etiology, and course of psychopathology because they account for patterns of relatedness among disorders that were once presumed distinct. Thus, these spectra represent alluring targets due to their comprehensive and parsimonious nature. Nevertheless, little research has established the role of individual disorders over and above broad dimensions in the study of psychopathology. In the current study, we investigate whether there are unique etiological associations between individual internalizing disorders and personality traits after accounting for their etiological associations with a broad internalizing dimension. We used a community sample of twins (Npairs = 448) ages 4 to 19 to examine the etiological associations between internalizing psychopathology and Big Five personality dimensions. In terms of genetic covariation, a broad internalizing dimension was positively associated with neuroticism and negatively associated with extraversion, agreeableness, and conscientiousness. Moreover, internalizing accounted for most of the genetic variance shared between individual internalizing disorders and personality traits. Nevertheless, there were unique genetic associations between the following pairs of personality traits and disorders: neuroticism and social anxiety, extraversion and social anxiety, agreeableness and depression, and conscientiousness and compulsions. There was little evidence of environmental influences shared between internalizing and personality. In sum, a broad internalizing dimension adequately accounted for almost all of the etiologic covariation between internalizing disorders and personality, with several interesting exceptions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

CBFA2T3-GLIS2 model of pediatric acute megakaryoblastic leukemia identifies FOLR1 as a CAR T cell target.

The CBFA2T3-GLIS2 (C/G) fusion is a product of a cryptic translocation primarily seen in infants and early childhood and is associated with dismal outcome. Here, we demonstrate that the expression of the C/G oncogenic fusion protein promotes the transformation of human cord blood hematopoietic stem and progenitor cells (CB HSPCs) in an endothelial cell coculture system that recapitulates the transcriptome, morphology, and immunophenotype of C/G acute myeloid leukemia (AML) and induces highly aggressive leukemia in xenograft models. Interrogating the transcriptome of C/G-CB cells and primary C/G AML identified a library of C/G-fusion-specific genes that are potential targets for therapy. We developed chimeric antigen receptor (CAR) T cells directed against one of the targets, folate receptor α (FOLR1), and demonstrated their preclinical efficacy against C/G AML using in vitro and xenograft models. FOLR1 is also expressed in renal and pulmonary epithelium, raising concerns for toxicity that must be addressed for the clinical application of this therapy. Our findings underscore the role of the endothelial niche in promoting leukemic transformation of C/G-transduced CB HSPCs. Furthermore, this work has broad implications for studies of leukemogenesis applicable to a variety of oncogenic fusion-driven pediatric leukemias, providing a robust and tractable model system to characterize the molecular mechanisms of leukemogenesis and identify biomarkers for disease diagnosis and targets for therapy.

Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk.

Genome-wide association studies (GWAS) identify genetic variants associated with a trait, regardless of how those variants are associated with the outcome. Characterizing whether variants for psychiatric outcomes operate via specific versus general pathways provides more informative measures of genetic risk. In the current analysis, we used multivariate GWAS to tease apart variants associated with problematic alcohol use (ALCP-total) through either a shared risk for externalizing (EXT) or a problematic alcohol use-specific risk (ALCP-specific). SNPs associated with ALCP-specific were primarily related to alcohol metabolism. Genetic correlations showed ALCP-specific was predominantly associated with alcohol use and other forms of psychopathology, but not other forms of substance use. Polygenic scores for ALCP-total were associated with multiple forms of substance use, but polygenic scores for ALCP-specific were only associated with alcohol phenotypes. Polygenic scores for both ALCP-specific and EXT show different patterns of associations with alcohol misuse across development. Our results demonstrate that focusing on both shared and specific risk can better characterize pathways of risk for substance use disorders. Parsing risk pathways will become increasingly relevant as genetic information is incorporated into clinical practice.

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

NOTCH1 signaling during CD4+ T-cell activation alters transcription factor networks and enhances antigen responsiveness.

Adoptive transfer of T cells expressing chimeric antigen receptors (CAR-T) effectively treats refractory hematologic malignancies in a subset of patients but can be limited by poor T-cell expansion and persistence in vivo. Less differentiated T-cell states correlate with the capacity of CAR-T to proliferate and mediate antitumor responses, and interventions that limit tumor-specific T-cell differentiation during ex vivo manufacturing enhance efficacy. NOTCH signaling is involved in fate decisions across diverse cell lineages and in memory CD8+ T cells was reported to upregulate the transcription factor FOXM1, attenuate differentiation, and enhance proliferation and antitumor efficacy in vivo. Here, we used a cell-free culture system to provide an agonistic NOTCH1 signal during naïve CD4+ T-cell activation and CAR-T production and studied the effects on differentiation, transcription factor expression, cytokine production, and responses to tumor. NOTCH1 agonism efficiently induced a stem cell memory phenotype in CAR-T derived from naïve but not memory CD4+ T cells and upregulated expression of AhR and c-MAF, driving heightened production of interleukin-22, interleukin-10, and granzyme B. NOTCH1-agonized CD4+ CAR-T demonstrated enhanced antigen responsiveness and proliferated to strikingly higher frequencies in mice bearing human lymphoma xenografts. NOTCH1-agonized CD4+ CAR-T also provided superior help to cotransferred CD8+ CAR-T, driving improved expansion and curative antitumor responses in vivo at low CAR-T doses. Our data expand the mechanisms by which NOTCH can shape CD4+ T-cell behavior and demonstrate that activating NOTCH1 signaling during genetic modification ex vivo is a potential strategy for enhancing the function of T cells engineered with tumor-targeting receptors.

Answering questions about the Hierarchical Taxonomy of Psychopathology (HiTOP): Analogies to whales and sharks miss the boat.

This commentary discusses questions and misconceptions about HiTOP raised by Haeffel et al. (2021). We explain what the system classifies and why it is descriptive and atheoretical, highlighting benefits and limitations of this approach. We clarify why the system is organized according to patterns of covariation or comorbidity among signs and symptoms of psychopathology, and we discuss how it is designed to be falsifiable and revised in a manner that is responsive to data. We refer to the body of evidence for HiTOP's external validity and for its scientific and clinical utility. We further describe how the system is currently used in clinics. In sum, many of Haeffel et al.'s concerns about HiTOP are unwarranted, and for those concerns that reflect real current limitations of HiTOP, our consortium is working to address them, with the aim of creating a nosology that is comprehensive and useful to both scientists and clinicians.

Engineering a niche supporting hematopoietic stem cell development using integrated single-cell transcriptomics.

Hematopoietic stem cells (HSCs) develop from hemogenic endothelium within embryonic arterial vessels such as the aorta of the aorta-gonad-mesonephros region (AGM). To identify the signals responsible for HSC formation, here we use single cell RNA-sequencing to simultaneously analyze the transcriptional profiles of AGM-derived cells transitioning from hemogenic endothelium to HSCs, and AGM-derived endothelial cells which provide signals sufficient to support HSC maturation and self-renewal. Pseudotemporal ordering reveals dynamics of gene expression during the hemogenic endothelium to HSC transition, identifying surface receptors specifically expressed on developing HSCs. Transcriptional profiling of niche endothelial cells identifies corresponding ligands, including those signaling to Notch receptors, VLA-4 integrin, and CXCR4, which, when integrated in an engineered platform, are sufficient to support the generation of engrafting HSCs. These studies provide a transcriptional map of the signaling interactions necessary for the development of HSCs and advance the goal of engineering HSCs for therapeutic applications.

Clarifying the structure and nature of left-wing authoritarianism.

Authoritarianism has been the subject of scientific inquiry for nearly a century, yet the vast majority of authoritarianism research has focused on right-wing authoritarianism. In the present studies, we investigate the nature, structure, and nomological network of left-wing authoritarianism (LWA), a construct famously known as "the Loch Ness Monster" of political psychology. We iteratively construct a measure and data-driven conceptualization of LWA across six samples (N = 7,258) and conduct quantitative tests of LWA's relations with more than 60 authoritarianism-related variables. We find that LWA, right-wing authoritarianism, and social dominance orientation reflect a shared constellation of personality traits, cognitive features, beliefs, and motivational values that might be considered the "heart" of authoritarianism. Relative to right-wing authoritarians, left-wing authoritarians were lower in dogmatism and cognitive rigidity, higher in negative emotionality, and expressed stronger support for a political system with substantial centralized state control. Our results also indicate that LWA powerfully predicts behavioral aggression and is strongly correlated with participation in political violence. We conclude that a movement away from exclusively right-wing conceptualizations of authoritarianism may be required to illuminate authoritarianism's central features, conceptual breadth, and psychological appeal. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Multipotent progenitors and hematopoietic stem cells arise independently from hemogenic endothelium in the mouse embryo.

During embryogenesis, waves of hematopoietic progenitors develop from hemogenic endothelium (HE) prior to the emergence of self-renewing hematopoietic stem cells (HSCs). Although previous studies have shown that yolk-sac-derived erythromyeloid progenitors and HSCs emerge from distinct populations of HE, it remains unknown whether the earliest lymphoid-competent progenitors, multipotent progenitors, and HSCs originate from common HE. In this study, we demonstrate by clonal assays and single-cell transcriptomics that rare HE with functional HSC potential in the early murine embryo are distinct from more abundant HE with multilineage hematopoietic potential that fail to generate HSCs. Specifically, HSC-competent HE are characterized by expression of CXCR4 surface marker and by higher expression of genes tied to arterial programs regulating HSC dormancy and self-renewal. Taken together, these findings suggest a revised model of developmental hematopoiesis in which the initial populations of multipotent progenitors and HSCs arise independently from HE with distinct phenotypic and transcriptional properties.

Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction.

Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.

Les progrès dans la réalisation de la classification quantitative de la psychopathologie.

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Downstream effects of polypathology on neurodegeneration of medial temporal lobe subregions.

The medial temporal lobe (MTL) is a nidus for neurodegenerative pathologies and therefore an important region in which to study polypathology. We investigated associations between neurodegenerative pathologies and the thickness of different MTL subregions measured using high-resolution post-mortem MRI. Tau, TAR DNA-binding protein 43 (TDP-43), amyloid-ß and α-synuclein pathology were rated on a scale of 0 (absent)-3 (severe) in the hippocampus and entorhinal cortex (ERC) of 58 individuals with and without neurodegenerative diseases (median age 75.0 years, 60.3% male). Thickness measurements in ERC, Brodmann Area (BA) 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare (SRLM) were derived from 0.2 × 0.2 × 0.2 mm3 post-mortem MRI scans of excised MTL specimens from the contralateral hemisphere using a semi-automated approach. Spearman's rank correlations were performed between neurodegenerative pathologies and thickness, correcting for age, sex and hemisphere, including all four proteinopathies in the model. We found significant associations of (1) TDP-43 with thickness in all subregions (r = - 0.27 to r = - 0.46), and (2) tau with BA35 (r = - 0.31) and SRLM thickness (r = - 0.33). In amyloid-ß and TDP-43 negative cases, we found strong significant associations of tau with ERC (r = - 0.40), BA35 (r = - 0.55), subiculum (r = - 0.42) and CA1 thickness (r = - 0.47). This unique dataset shows widespread MTL atrophy in relation to TDP-43 pathology and atrophy in regions affected early in Braak stageing and tau pathology. Moreover, the strong association of tau with thickness in early Braak regions in the absence of amyloid-ß suggests a role of Primary Age-Related Tauopathy in neurodegeneration.