Biology subjects

Auluck, P.

Publications and source records attributed to Auluck, P..

7 recordsLinked to original sources

bioRxiv2025

Long-Read epigenetic clocks identify improved brain aging predictions

Epigenetic clocks are widely used to estimate biological aging, yet most are built from array-based data from peripheral tissues of predominantly European-ancestry individuals, limiting their generalizability. Here, we present aging clocks on DNA methylation from Oxford Nanopore long-read sequencing (LRS), leveraging over 28 million CpG sites from prefrontal cortex samples across individuals of African and European ancestry. These models were developed using GenoML, an automated machine learning platform for multi-omics data that leverages a diverse catalog of existing model architectures. Our long-read-informed clocks were developed using promoter-based and whole-genome window-based features, yielding models for each individual cohort as well as a combined-cohort clock. Each of these models demonstrated favorable performance compared to existing methylation clocks and was externally validated in a cohort of Colombian individuals. We further performed enrichment analyses and nominated both shared and cohort-specific pathways, cell types, and transcription factor binding motifs which may be implicated in aging and were not fully explained by cell type proportions or postmortem interval. Altogether, our findings highlight the power of long-read methylation data for constructing accurate, ancestry-aware aging clocks and emphasize the importance of inclusive training datasets.

bioinformatics↗

bioRxiv2025

Sex effects on gene expression across the human cerebral cortex at single cell resolution

Sex differences in brain-related health outcomes may be a consequence of differences in gene expression. However, most current knowledge relies on studies of bulk tissue or isolated brain regions. Here, we present a large-scale single-cell analysis of transcriptomic sex differences in the human brain, using 169 samples from 15 females and 15 males across six cortical regions, selected based on in vivo neuroimaging measures of sex-biased volume. We find that sex effects on gene expression are highly patterned across cortical regions, cell types, and genes. They are most pronounced in: i) multiple cell types in the fusiform cortex (linked to male-biased volume and sex-biased behaviors); ii) oligodendrocytes, astrocytes, and excitatory neurons across regions; and iii) a subset of sex chromosome and autosomal genes. Over 3,000 unique genes exhibit sex-biased expression, with 133 genes (119 autosomal) showing consistent sex differences across all region x cell type combinations. Sex chromosome genes show the largest sex differences in expression, driven by conserved X-Y gametologs, cell-type-specific biases in certain X- and Y-linked genes, and escape from X-inactivation - with the list of known escapees substantially expanded through our single-cell allele-specific expression analysis. Broader effects of sex on autosomal expression are captured in 13 core signatures with varying cell type vs. region specificity. These signatures are: i) shaped by regional differences in metabolism and laminar architecture; ii) enriched for diverse cellular compartments and biological processes; iii) regulated by sex steroids and X-linked transcription factors; and iv) linked to sex-specific genetic risk factors in sex-biased neuropsychiatric and neurodegenerative diseases. This study substantially advances the breadth, depth, and granularity of knowledge on sex differences in the human brain, and provides a new open data resource to support future research.

neuroscience↗

bioRxiv2025

Haplotype-Resolved DNA Methylation at the APOE Locus identifies Allele-Specific Epigenetic Signatures Relevant to Alzheimer's Disease Risk

The APOE gene encodes a key lipid transport protein and plays a central role in Alzheimers disease (AD) pathogenesis. Three common APOE alleles, {varepsilon}2 (rs7412(C>T), {varepsilon}3 (reference), and {varepsilon}4 (rs429358(T>C)), arise from two coding variants in exon 4 and confer distinct AD risk profiles, with {varepsilon}4 increasing risk and {varepsilon}2 providing protection. The {varepsilon}3-linked APOE variant rs769455[T] has also been associated with elevated AD risk in individuals of African ancestry carrying both rs769455[T] and {varepsilon}4 alleles. These single nucleotide variants (SNVs) reside in a cytosine-phosphate-guanine (CpG) island, which is a region with a higher frequency of CpG sites compared to the rest of the genome. CpG sites are subject to 5-methylcytosine (5mC) methylation by DNA methyltransferases which add a methyl group to the fifth carbon on the cytosine residue of a CpG site. The presence of SNVs can disrupt this process, making these regions prime targets for differential methylation; however, allele-specific methylation patterns in APOE remain poorly resolved due to technical limitations of conventional bisulfite and methylation array based methods, including degraded DNA quality, sparse CpG coverage, and lack of haplotype phasing. Here, we leverage high-accuracy long-read sequencing data to generate haplotype-resolved methylation profiles of the APOE locus in 332 postmortem brain samples from two ancestrally different cohorts. This includes 201 individuals of European ancestry from the North American Brain Expression Consortium (NABEC), comprising 402 haplotypes (48 {varepsilon}2 and 58 {varepsilon}4 alleles), and 131 individuals of African and African admixed ancestry from the Human Brain Core Collection (HBCC), comprising 262 haplotypes (25 {varepsilon}2, 64 {varepsilon}4, and 7 rs769455 alleles). A linear regression analysis identified 18 novel differentially methylated CpG sites (DMCs) associated with APOE {varepsilon}2, {varepsilon}4, and rs769455 within a gene cluster spanning TOMM40, APOE, APOC1, and APOC4-APOC2. This represents the most comprehensive haplotype-resolved methylation study of APOE in human brain tissue to date. Our results uncover distinct allele-specific methylation signatures and demonstrate the power of long-read sequencing for resolving epigenetic variation relevant to AD risk.

genomics↗

bioRxiv2024

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.

genomics↗

bioRxiv2024

High-risk neuropsychiatric copy number variants are associated with convergent transcriptomic changes in human brain cells

Large, recurrent copy number variants (CNVs) are among the strongest risk factors for neuropsychiatric conditions, contributing to multiple phenotypes with overlapping psychiatric and cognitive symptoms. However, the molecular basis of this convergent risk remains unknown. We evaluated the human brain transcriptome in carriers of nine high-risk neuropsychiatric CNVs and matched non-carriers using single nucleus RNA-sequencing. Brain tissue from carriers displayed widespread disruptions of gene expression, with thousands of differentially expressed genes, mostly located outside of the respective CNV regions. There were greater changes in deletions compared to reciprocal duplications. Functional enrichment analysis revealed changes in mitochondrial energy metabolism and synaptic function that converged across CNVs and cell types. For mirror CNVs, the direction of effects was often reversed between deletions and duplications and showed correlation with CNV gene dosage. These findings suggest that a shared pathophysiology underlies risk for convergent brain phenotypes across CNVs and point toward promising therapeutic targets.

genetics↗

bioRxiv2024

Postmortem tissue biomarkers of menopausal transition

The menopausal transition (MT) is associated with an increased risk for many disorders including neurological and mental disorders. Brain imaging studies in living humans show changes in brain metabolism and structure that may contribute to the MT-associated brain disease risk. Although deficits in ovarian hormones have been implicated, cellular and molecular studies of the brain undergoing MT are currently lacking, mostly due to a difficulty in studying MT in postmortem human brain. To enable this research, we explored 39 candidate biomarkers for menopausal status in 42 pre-, peri-, and post-menopausal subjects across three postmortem tissues: blood, the hypothalamus, and pituitary gland. We identified thirteen significant and seven strongest menopausal biomarkers across the three tissues. Using these biomarkers, we generated multi-tissue and tissue-specific composite measures that allow the postmortem identification of the menopausal status across different age ranges, including the "perimenopausal", 45-55-year-old group. Our findings enable the study of cellular and molecular mechanisms underlying increased neuropsychiatric risk during the MT, opening the path for hormone status-informed, precision medicine approach in womens mental health.

neuroscience↗

bioRxiv2023

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗