Genetic architecture of the structural connectome.

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

CHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer's disease.

Changes in high-affinity nicotinic acetylcholine receptors are intricately connected to neuropathology in Alzheimer's Disease (AD). Protective and cognitive-enhancing roles for the nicotinic α5 subunit have been identified, but this gene has not been closely examined in the context of human aging and dementia. Therefore, we investigate the nicotinic α5 gene CHRNA5 and the impact of relevant single nucleotide polymorphisms (SNPs) in prefrontal cortex from 922 individuals with matched genotypic and post-mortem RNA sequencing in the Religious Orders Study and Memory and Aging Project (ROS/MAP). We find that a genotype robustly linked to increased expression of CHRNA5 (rs1979905A2) predicts significantly reduced cortical ß-amyloid load. Intriguingly, co-expression analysis suggests CHRNA5 has a distinct cellular expression profile compared to other nicotinic receptor genes. Consistent with this prediction, single nucleus RNA sequencing from 22 individuals reveals CHRNA5 expression is disproportionately elevated in chandelier neurons, a distinct subtype of inhibitory neuron known for its role in excitatory/inhibitory (E/I) balance. We show that chandelier neurons are enriched in amyloid-binding proteins compared to basket cells, the other major subtype of PVALB-positive interneurons. Consistent with the hypothesis that nicotinic receptors in chandelier cells normally protect against ß-amyloid, cell-type proportion analysis from 549 individuals reveals these neurons show amyloid-associated vulnerability only in individuals with impaired function/trafficking of nicotinic α5-containing receptors due to homozygosity of the missense CHRNA5 SNP (rs16969968A2). Taken together, these findings suggest that CHRNA5 and its nicotinic α5 subunit exert a neuroprotective role in aging and Alzheimer's disease centered on chandelier interneurons.

Integrating single-cell and spatially resolved transcriptomic strategies to survey the astrocyte response to stroke in male mice.

Astrocytes, a type of glial cell in the central nervous system (CNS), adopt diverse states in response to injury that are influenced by their location relative to the insult. Here, we describe a platform for spatially resolved, single-cell transcriptomics and proteomics, called tDISCO (tissue-digital microfluidic isolation of single cells for -Omics). We use tDISCO alongside two high-throughput platforms for spatial (Visium) and single-cell transcriptomics (10X Chromium) to examine the heterogeneity of the astrocyte response to a cortical ischemic stroke in male mice. We show that integration of Visium and 10X Chromium datasets infers two astrocyte populations, proximal or distal to the injury site, while tDISCO determines the spatial boundaries and molecular profiles that define these populations. We find that proximal astrocytes show differences in lipid shuttling, with enriched expression of Apoe and Fabp5. Our datasets provide a resource for understanding the roles of astrocytes in stroke and showcase the utility of tDISCO for hypothesis-driven, spatially resolved single-cell experiments.

Opposing brain signatures of sleep in task-based and resting-state conditions.

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature.

Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue.

Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse patch-seq datasets.

Microglia are cells with diverse roles, including the regulation of neuronal excitability. We leveraged Patch-seq to assess the presence and effects of microglia in the local microenvironment of recorded neurons. We first quantified the amounts of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons, observing extensive contamination. Variation in microglial contamination was explained foremost by donor identity, particularly in human samples, and additionally by neuronal cell type identity in mice. Gene set enrichment analysis suggests that microglial contamination is reflective of activated microglia, and that these transcriptional signatures are distinct from those captured via single-nucleus RNA-seq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results generalize beyond Patch-seq to suggest that activated microglia may be widely present across brain slice preparations and contribute to neuron- and donor-related electrophysiological variability in vitro.

Shared genetic risk loci between Alzheimer's disease and related dementias, Parkinson's disease, and amyotrophic lateral sclerosis.

BACKGROUND: Genome-wide association studies (GWAS) have indicated moderate genetic overlap between Alzheimer's disease (AD) and related dementias (ADRD), Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS), neurodegenerative disorders traditionally considered etiologically distinct. However, the specific genetic variants and loci underlying this overlap remain almost entirely unknown. METHODS: We leveraged state-of-the-art GWAS for ADRD, PD, and ALS. For each pair of disorders, we examined each of the GWAS hits for one disorder and tested whether they were also significant for the other disorder, applying Bonferroni correction for the number of variants tested. This approach rigorously controls the family-wise error rate for both disorders, analogously to genome-wide significance. RESULTS: Eleven loci with GWAS hits for one disorder were also associated with one or both of the other disorders: one with all three disorders (the MAPT/KANSL1 locus), five with ADRD and PD (near LCORL, CLU, SETD1A/KAT8, WWOX, and GRN), three with ADRD and ALS (near GPX3, HS3ST5/HDAC2/MARCKS, and TSPOAP1), and two with PD and ALS (near GAK/TMEM175 and NEK1). Two of these loci (LCORL and NEK1) were associated with an increased risk of one disorder but decreased risk of another. Colocalization analysis supported a shared causal variant between ADRD and PD at the CLU, WWOX, and LCORL loci, between ADRD and ALS at the TSPOAP1 locus, and between PD and ALS at the NEK1 and GAK/TMEM175 loci. To address the concern that ADRD is an imperfect proxy for AD and that the ADRD and PD GWAS have overlapping participants (nearly all of which are from the UK Biobank), we confirmed that all our ADRD associations had nearly identical odds ratios in an AD GWAS that excluded the UK Biobank, and all but one remained nominally significant (p < 0.05) for AD. CONCLUSIONS: In one of the most comprehensive investigations to date of pleiotropy between neurodegenerative disorders, we identify eleven genetic risk loci shared among ADRD, PD, and ALS. These loci support lysosomal/autophagic dysfunction (GAK/TMEM175, GRN, KANSL1), neuroinflammation/immunity (TSPOAP1), oxidative stress (GPX3, KANSL1), and the DNA damage response (NEK1) as transdiagnostic processes underlying multiple neurodegenerative disorders.

Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease.

Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.

Identification of brain cell types underlying genetic association with word reading and correlated traits.

Neuroimaging studies implicate multiple cortical regions in reading ability/disability. However, the neural cell types integral to the reading process are unknown. To contribute to this gap in knowledge, we integrated genetic results from genome-wide association studies for word reading (n = 5054) with gene expression datasets from adult/fetal human brain. Linkage disequilibrium score regression (LDSC) suggested that variants associated with word reading were enriched in genes expressed in adult excitatory neurons, specifically layer 5 and 6 FEZF2 expressing neurons and intratelencephalic (IT) neurons, which express the marker genes LINC00507, THEMIS, or RORB. Inhibitory neurons (VIP, SST, and PVALB) were also found. This finding was interesting as neurometabolite studies previously implicated excitatory-inhibitory imbalances in the etiology of reading disabilities (RD). We also tested traits that shared genetic etiology with word reading (previously determined by polygenic risk scores): attention-deficit/hyperactivity disorder (ADHD), educational attainment, and cognitive ability. For ADHD, we identified enrichment in L4 IT adult excitatory neurons. For educational attainment and cognitive ability, we confirmed previous studies identifying multiple subclasses of adult cortical excitatory and inhibitory neurons, as well as astrocytes and oligodendrocytes. For educational attainment and cognitive ability, we also identified enrichment in multiple fetal cortical excitatory and inhibitory neurons, intermediate progenitor cells, and radial glial cells. In summary, this study supports a role of excitatory and inhibitory neurons in reading and excitatory neurons in ADHD and contributes new information on fetal cell types enriched in educational attainment and cognitive ability, thereby improving our understanding of the neurobiological basis of reading/correlated traits.

Chrna5 and lynx prototoxins identify acetylcholine super-responder subplate neurons.

Attention depends on cholinergic excitation of prefrontal neurons but is sensitive to perturbation of α5-containing nicotinic receptors encoded by Chrna5. However, Chrna5-expressing (Chrna5+) neurons remain enigmatic, despite their potential as a target to improve attention. Here, we generate complex transgenic mice to probe Chrna5+ neurons and their sensitivity to endogenous acetylcholine. Through opto-physiological experiments, we discover that Chrna5+ neurons contain a distinct population of acetylcholine super-responders. Leveraging single-cell transcriptomics, we discover molecular markers conferring subplate identity on this subset. We determine that Chrna5+ super-responders express a unique complement of GPI-anchored lynx prototoxin genes (Lypd1, Ly6g6e, and Lypd6b), predicting distinct nicotinic receptor regulation. To manipulate lynx regulation of endogenous nicotinic responses, we developed a pharmacological strategy guided by transcriptomic predictions. Overall, we reveal Chrna5-Cre mice as a transgenic tool to target the diversity of subplate neurons in adulthood, yielding new molecular strategies to manipulate their cholinergic activation relevant to attention disorders.

Robust differences in cortical cell type proportions across healthy human aging inferred through cross-dataset transcriptome analyses.

Age-related declines in cognitive function are driven by cell type-specific changes in the brain. However, it remains challenging to study cellular differences associated with healthy aging as traditional approaches scale poorly to the sample sizes needed to capture aging and cellular heterogeneity. Here, we employed cellular deconvolution to estimate relative cell type proportions using frontal cortex bulk gene expression from individuals without psychiatric conditions or brain pathologies. Our analyses comprised 8 datasets and 6 cohorts (1142 subjects and 1429 samples) with ages of death spanning 15-90 years. We found aging associated with profound differences in cellular proportions, with the largest changes reflecting fewer somatostatin- and vasoactive intestinal peptide-expressing interneurons, more astrocytes and other non-neuronal cells, and a suggestive "U-shaped" quadratic relationship for microglia. Cell type associations with age were markedly robust across bulk-and single nucleus datasets. Altogether, we present a comprehensive account of proportional differences in cortical cell types associated with healthy aging.

Fragmentation of rest periods, astrocyte activation, and cognitive decline in older adults with and without Alzheimer's disease.

INTRODUCTION: Sleep disruption is associated with astrocyte activation and impaired cognition in model organisms. However, the relationship among sleep, astrocyte activation, and cognition in humans is uncertain. METHODS: We used RNA-seq to quantify the prefrontal cortex expression of a panel of human activated astrocyte marker genes in 1076 older adults in the Religious Orders Study and Rush Memory and Aging Project, 411 of whom had multi-day actigraphy prior to death. We related this to rest fragmentation, a proxy for sleep fragmentation, and to longitudinal cognitive function. RESULTS: Fragmentation of rest periods was associated with higher expression of activated astrocyte marker genes, which was associated with a lower level and faster decline of cognitive function. DISCUSSION: Astrocyte activation and fragmented rest are associated with each other and with accelerated cognitive decline. If experimental studies confirm a causal relationship, targeting sleep fragmentation and astrocyte activation may benefit cognition in older adults. HIGHLIGHTS: Greater fragmentation of rest periods, a proxy for sleep fragmentation, is associated with higher composite expression of a panel of genes characteristic of activated astrocytes. Increased expression of genes characteristic of activated astrocytes was associated with a lower level and more rapid decline of cognitive function, beyond that accounted for by the burden of amyloid and neurofibrillary tangle pathology. Longitudinal and experimental studies are needed to delineate the causal relationships among sleep, astrocyte activation, and cognition.

Association analyses of the autosomal genome and mitochondrial DNA with accelerometry-derived sleep parameters in depressed UK biobank subjects.

BACKGROUND: The bidirectional relationship between sleep disturbances and depression is well documented, yet the biology of sleep is not fully understood. Mitochondria have become of interest not only because of the connection between sleep and metabolism but also because of mitochondria's involvement in the production of reactive oxygen species, which are largely scavenged during sleep. METHODS: Genome-wide association studies (GWAS) of eight accelerometry-derived sleep measures were performed across both the autosomal and mitochondrial DNA (mtDNA) among two severity levels of depression in UK Biobank participants. We calculated SNP heritability for each of the sleep measures. Linear regression was performed to test associations and mitochondrial haplogroups. RESULTS: Variants included in the GWAS accounted for moderate heritability of bedtime (19.6%, p = 4.75 × 10-7), sleep duration (16.6%, p = 8.58 × 10-6) and duration of longest sleep bout (22.6%, p = 4.64 × 10-4). No variants passed genome-wide significance in the autosomal genome. The top hit in the severe depression sample was rs145019802, near GOLGA8B, for sleep efficiency (p = 1.17 × 10-7), and the top hit in the broad depression sample was rs7100859, an intergenic SNP, and nap duration (p = 1.25 × 10-7). Top mtDNA loci were m.12633C > A of MT-ND5 with bedtime (p = 0.002) in the severe sample and m.16186C > T of the control region with nap duration (p = 0.002) in the broad sample. CONCLUSION: SNP heritability estimates support the involvement of common SNPs in specific sleep measures among depressed individuals. This is the first study to analyze mtDNA variance in sleep measures in depressed individuals. Our mtDNA findings, although nominally significant, provide preliminary suggestion that mitochondria are involved in sleep.

Symptom dimensions of major depression in a large community-based cohort.

BACKGROUND: Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. METHODS: This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or 'symptom dimensions' via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. RESULTS: Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. CONCLUSIONS: An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

Age-dependent increased sag amplitude in human pyramidal neurons dampens baseline cortical activity.

Aging involves various neurobiological changes, although their effect on brain function in humans remains poorly understood. The growing availability of human neuronal and circuit data provides opportunities for uncovering age-dependent changes of brain networks and for constraining models to predict consequences on brain activity. Here we found increased sag voltage amplitude in human middle temporal gyrus layer 5 pyramidal neurons from older subjects and captured this effect in biophysical models of younger and older pyramidal neurons. We used these models to simulate detailed layer 5 microcircuits and found lower baseline firing in older pyramidal neuron microcircuits, with minimal effect on response. We then validated the predicted reduced baseline firing using extracellular multielectrode recordings from human brain slices of different ages. Our results thus report changes in human pyramidal neuron input integration properties and provide fundamental insights into the neuronal mechanisms of altered cortical excitability and resting-state activity in human aging.

An in vitro whole-cell electrophysiology dataset of human cortical neurons.

BACKGROUND: Whole-cell patch-clamp electrophysiology is an essential technique for understanding how single neurons translate their diverse inputs into a functional output. The relative inaccessibility of live human cortical neurons for experimental manipulation has made it difficult to determine the unique features of how human cortical neurons differ from their counterparts in other species. FINDINGS: We present a curated repository of whole-cell patch-clamp recordings from surgically resected human cortical tissue, encompassing 118 neurons from 35 individuals (age range, 21-59 years; 17 male, 18 female). Recorded human cortical neurons derive from layers 2 and 3 (L2&3), deep layer 3 (L3c), or layer 5 (L5) and are annotated with a rich set of subject and experimental metadata. For comparison, we also provide a limited set of comparable recordings from 21-day-old mice (11 cells from 5 mice). All electrophysiological recordings are provided in the Neurodata Without Borders (NWB) format and are available for further analysis via the Distributed Archives for Neurophysiology Data Integration online repository. The associated data conversion code is made publicly available and can help others in converting electrophysiology datasets to the open NWB standard for general reuse. CONCLUSION: These data can be used for novel analyses of biophysical characteristics of human cortical neurons, including in cross-species or cross-lab comparisons or in building computational models of individual human neurons.

Sex-specific associations between lifetime diagnosis of bipolar disorder and cardiovascular disease: A cross-sectional analysis of 257,673 participants from the UK Biobank.

BACKGROUND: Sex is seldom considered as a potential moderator of the impact of bipolar disorder (BD) on cardiovascular disease (CVD) risk. We aimed to characterize the sex-specific association of CVD and BD using data from the UK Biobank. METHODS: In a cross-sectional analysis, we compared the odds ratio between women and men with BD for seven CVD diagnoses (coronary artery disease, myocardial infarction, angina, atrial fibrillation, heart failure, stroke, and essential hypertension) and four cardiovascular biomarkers (arterial stiffness index, low-density lipoprotein, C-reactive protein, and HbA1c) in 293 participants with BD and 257,380 psychiatrically healthy controls in the UK Biobank. RESULTS: After adjusting for age, we found a two- to three-fold stronger association among women than among men between BD and rates of coronary artery disease, heart failure, and essential hypertension, with a significant sex-by-diagnosis interactions. The association remained significant after controlling for self-reported race, education, income, and smoking status. After controlling for potential confounders, there was no significant association between sex and any cardiovascular biomarkers. LIMITATIONS: These analyses could not disentangle effects of BD from its treatment. CONCLUSIONS: Our results underscore the importance of incorporating sex and mental illness in risk estimation tools for CVD, and improving screening for, and timely treatment of, CVD in those with BD. Future research is needed to better understand the contributors and mechanisms of sex differences related to CVD risk in BD.

Identification of Endocannabinoid Predictors of Treatment Outcomes in Major Depressive Disorder: A Secondary Analysis of the First Canadian Biomarker Integration Network in Depression (CAN-BIND 1) Study.

INTRODUCTION: An increasing number of studies are examining the link between the endocannabinoidome and major depressive disorder (MDD). We conducted an exploratory analysis of this system to identify potential markers of treatment outcomes. METHODS: The dataset of the Canadian Biomarker Integration Network in Depression-1 study, consisting of 180 patients with MDD treated for eight weeks with escitalopram followed by eight weeks with escitalopram alone or augmented with aripiprazole was analyzed. Association between response Montgomery-Asberg Depression Rating Scale (MADRS; score reduction≥50%) or remission (MADRS score≤10) at weeks 8 and 16 and single nucleotide polymorphisms (SNPs), methylation, and mRNA levels of 33 endocannabinoid markers were examined. A standard genome-wide association studies protocol was used for identifying SNPs, and logistic regression was used to assess methylation and mRNA levels. RESULTS: Lower methylation of CpG islands of the diacylglycerol lipase alpha gene (DAGLA) was associated with non-remission at week 16 (DAGLA; OR=0.337, p<0.003, q=0.050). Methylation of DAGLA was correlated with improvement in Clinical Global Impression (p=0.026), Quick Inventory of Depressive Symptomatology (p=0.010), and Snaith-Hamilton Pleasure scales (p=0.028). We did not find any association between SNPs or mRNA levels and treatment outcomes. DISCUSSION: Methylation of DAGLA is a promising candidate as a marker of treatment outcomes for MDD and needs to be explored further.

Bulk and Single-Nucleus Transcriptomics Highlight Intra-Telencephalic and Somatostatin Neurons in Alzheimer's Disease.

Cortical neuron loss is a pathological hallmark of late-onset Alzheimer's disease (AD). However, it remains unclear which neuronal subtypes beyond broad excitatory and inhibitory classes are most vulnerable. Here, we analyzed cell subtype proportion differences in AD compared to non-AD controls using 1037 post-mortem brain samples from six neocortical regions. We identified the strongest associations of AD with fewer somatostatin (SST) inhibitory neurons (ß = -0.48, p bonf = 8.98 × 10-9) and intra-telencephalic (IT) excitatory neurons (ß = -0.45, p bonf = 4.32 × 10-7). Replication in three AD case-control single-nucleus RNAseq datasets most strongly supported the bulk tissue association of fewer SST neurons in AD. In depth analyses of cell type proportions with specific AD-related neuropathological and cognitive phenotypes revealed fewer SST neurons with greater brain-wide post-mortem tau and beta amyloid, as well as a faster rate of antemortem cognitive decline. In contrast, greater IT neuron proportions were associated with a slower rate of cognitive decline as well as greater residual cognition-a measure of cognitive resilience-but not canonical AD neuropathology. Our findings implicate somatostatin inhibitory and intra-telencephalic excitatory neuron subclasses in the pathogenesis of AD and in cognitive resilience to AD pathology, respectively.

Multiscale neural signatures of major depressive, anxiety, and stress-related disorders.

The extent of shared and distinct neural mechanisms underlying major depressive disorder (MDD), anxiety, and stress-related disorders is still unclear. We compared the neural signatures of these disorders in 5,405 UK Biobank patients and 21,727 healthy controls. We found the greatest case­control differences in resting-state functional connectivity and cortical thickness in MDD, followed by anxiety and stress-related disorders. Neural signatures for MDD and anxiety disorders were highly concordant, whereas stress-related disorders showed a distinct pattern. Controlling for cross-disorder genetic risk somewhat decreased the similarity between functional neural signatures of stress-related disorders and both MDD and anxiety disorders. Among cases and healthy controls, reduced within-network and increased between-network frontoparietal and default mode connectivity were associated with poorer cognitive performance (processing speed, attention, associative learning, and fluid intelligence). These results provide evidence for distinct neural circuit function impairments in MDD and anxiety disorders compared to stress disorders, yet cognitive impairment appears unrelated to diagnosis and varies with circuit function.