Assigning function to SNPs: Considerations when interpreting genetic variation.

Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precision medicine. However, despite the apparent simplicity that is captured in the name SNP - 'single nucleotide' changes are not easy to functionally characterize. This complexity arises from multiple features of the genome including the fact that function is development and environment specific. As such, we are often fooled by our terminology and underlying assumptions that there is a single function for a SNP. Here we discuss some of what is known about SNPs, their functions and how we can go about characterizing them.

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes.

BACKGROUND: To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored. METHODS: We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity. RESULTS: We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers. CONCLUSIONS: Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Spatially constrained gene regulation identifies key genetic contributions of preeclampsia, hypertension, and proteinuria†.

Preeclampsia (PE) is a relatively common but severe pregnancy disorder (with very limited effective treatments) characterized by hypertension (HTN) and usually proteinuria (PRO) or other organ damage. Genome-wide association studies (GWAS) of PE, HTN, and PRO have mostly identified risk loci single nucleotide polymorphisms (SNPs) located in noncoding genomic regions, likely impacting the regulation of distal gene expression. The latest GWAS associated (P < 1 × 10-6) SNPs to PE (n = 25), HTN (n = 1926), and PRO (n = 170). Our algorithmic analysis (CoDeS3D) used chromatin connection data (Hi-C) derived from 70 cell lines followed by analysis of two expression quantitative trail loci (eQTL) cohorts: GTEx (838 donors, 54 tissues, totaling 15 253 samples) and DICE (91 donors, 13 blood tissue types). We identified spatially constrained eQTLs which implicate gene targets in PE (n = 16), HTN (n = 3561), and PRO (n = 335). By overlapping these target genes and their molecular pathways (protein-protein interaction networks), we identified shared functional impacts between PE and HTN, which are significantly enriched for regulatory interactions which target genes intolerant to loss-of-function mutations. While the disease-associated SNP loci mostly do not overlap, the regulatory signals (target genes and pathways) overlap, informing on PE risk mechanisms. This demonstrates a model in which genetic predisposition to HTN and PRO lays a molecular groundwork toward risk for PE pathogenesis. This overlap at the gene regulatory network level identifies possible shared therapeutic targets for future study.

Establishing gene regulatory networks from Parkinson's disease risk loci.

The latest meta-analysis of genome-wide association studies identified 90 independent variants across 78 genomic regions associated with Parkinson's disease, yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with Parkinson's disease risk variants, we utilized an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci) data. We identified 518 genes subject to regulation by 76 Parkinson's variants across 49 tissues, whicih encompass 36 peripheral and 13 CNS tissues. Notably, one-third of these genes were regulated via trans-acting mechanisms (distal; risk locus-gene separated by >1 Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-expression quantitative trait loci-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and Parkinson's disease genome-wide association studies loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neurodevelopment-specific expression quantitative trait loci-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of Parkinson's disease. Through utilizing Louvain clustering we extracted nine significant and highly intraconnected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with Parkinson's disease. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of Parkinson's disease variants, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of Parkinson's disease.

Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways.

BACKGROUND: The cohesin complex plays an essential role in genome organisation and cell division. A full complement of the cohesin complex and its regulators is important for normal development, since heterozygous mutations in genes encoding these components can be sufficient to produce a disease phenotype. The implication that genes encoding the cohesin subunits or cohesin regulators must be tightly controlled and resistant to variability in expression has not yet been formally tested. METHODS: Here, we identify spatial-regulatory connections with potential to regulate expression of cohesin loci (Mitotic: SMC1A, SMC3, STAG1, STAG2, RAD21/RAD21-AS; Meiotic: SMC1B, STAG3, REC8, RAD21L1), cohesin-ring support genes (NIPBL, MAU2, WAPL, PDS5A, PDS5B) and CTCF, including linking their expression to that of other genes. We searched the genome-wide association studies (GWAS) catalogue for SNPs mapped or attributed to cohesin genes by GWAS (GWAS-attributed) and the GTEx catalogue for SNPs mapped to cohesin genes by cis-regulatory variants in one or more of 44 tissues across the human body (expression quantitative trail locus-attributed). RESULTS: Connections that centre on the cohesin ring subunits provide evidence of coordinated regulation that has little tolerance for perturbation. We used the CoDeS3D SNP-gene attribution methodology to identify transcriptional changes across a set of genes coregulated with the cohesin loci that include biological pathways such as extracellular matrix production and proteasome-mediated protein degradation. Remarkably, many of the genes that are coregulated with cohesin loci are themselves intolerant to loss-of-function. CONCLUSIONS: The results highlight the importance of robust regulation of cohesin genes and implicate novel pathways that may be important in the human cohesinopathy disorders.

A systematic review of asthma case definitions in 67 birth cohort studies.

BACKGROUND: Birth cohort studies are a valuable source of information about potential risk factors for childhood asthma. To better understand similarities and variations in findings between birth cohort studies, the methodologies used to measure asthma require consideration. OBJECTIVE: To review and appraise the definitions of "asthma" used in birth cohort studies. METHODS: A literature search, conducted in December 2017 in the MEDLINE database and birth cohort repositories, identified 1721 citations published since 1990. Information extracted included: study name, year of publication, sample size, sample age, prevalence of asthma (%), study region, source of information about asthma, measured outcome, and asthma case definition. A meta-analysis evaluated whether asthma prevalence in cohorts from Europe and North America varied by the studies' definition of asthma and by their data sources. RESULTS: The final review included 67 birth cohorts, of which 48 (72%) were from Europe, 14 (21%) from North America, 3 (5%) from Oceania, 1 (1%) from Asia and 1 (1%) from South America. We identified three measured outcomes: "asthma ever", "current asthma", and "asthma" without further specification. Definitions of "asthma ever" were primarily based upon an affirmative parental response to the question whether the child had ever been diagnosed with asthma by a physician. The most frequently used definition of "current asthma" was "asthma ever" and either asthma symptoms or asthma medications in the last 12 months. This definition of "current asthma" was used in 16 cohorts. There was no statistically significant difference in the pooled asthma prevalence in European and North American cohorts that used questionnaire alone versus other data sources to classify asthma. CONCLUSION: There is substantial heterogeneity in childhood asthma definitions in birth cohort studies. Standardisation of asthma case definitions will improve the comparability and utility of future cohort studies and enable meta-analyses.

Common Variants Coregulate Expression of GBA and Modifier Genes to Delay Parkinson's Disease Onset.

BACKGROUND: GBA mutations are numerically the most significant genetic risk factor for Parkinson's disease (PD), yet these mutations have low penetrance, suggesting additional mechanisms. OBJECTIVES: The objective of this study was to determine if the penetrance of GBA in PD can be explained by regulatory effects on GBA and modifier genes. METHODS: Genetic variants associated with the regulation of GBA were identified by screening 128 common single nucleotide polymorphisms (SNPs) in the GBA locus for spatial cis-expression quantitative trail locus (supported by chromatin interactions). RESULTS: We identified common noncoding SNPs within GBA that (1) regulate GBA expression in peripheral tissues, some of which display α-synuclein pathology and (2) coregulate potential modifier genes in the central nervous system and/or peripheral tissues. Haplotypes based on 3 of these SNPs delay disease onset by 5 years. In addition, SNPs on 6 separate chromosomes coregulate GBA expression specifically in either the substantia nigra or cortex, and their combined effect potentially modulates motor and cognitive symptoms, respectively. CONCLUSIONS: This work provides a new perspective on the haplotype-specific effects of GBA and the genetic etiology of PD, expanding the role of GBA from the gene encoding the ß-glucocerebrosidase (GCase) to that of a central regulator and modifier of PD onset, with GBA expression itself subject to distant regulation. Some idiopathic patients might possess insufficient GBA-encoded GCase activity in the substantia nigra as the result of distant regulatory variants and therefore might benefit from GBA-targeting therapeutics. The SNPs' regulatory impacts provide a plausible explanation for the variable phenotypes also observed in GBA-centric Gaucher's disease and dementia with Lewy bodies. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, LLC on behalf of International Parkinson and Movement Disorder Society.

Transcriptional profiling of the zebrafish proximal tubule.

The hepatocyte nuclear factor-1ß (Hnf1b) transcription factor is a key regulator of kidney tubule formation and is associated with a syndrome of renal cysts and early onset diabetes. To further our understanding of Hnf1b in the developing zebrafish kidney, we performed RNA sequencing analysis of proximal tubules from hnf1b-deficient larvae. This analysis revealed an enrichment of gene transcripts encoding transporters of the solute carrier (SLC) superfamily, including multiple members of slc2 and slc5 glucose transporters. An investigation of expression of slc2a1a, slc2a2, and slc5a2 as well as a poorly studied glucose/mannose transporter encoded by slc5a9 revealed that these genes undergo dynamic spatiotemporal changes during tubule formation and maturation. A comparative analysis of zebrafish SLC genes with those expressed in mouse proximal tubules showed a substantial overlap at the level of gene families, indicating a high degree of functional conservation between zebrafish and mammalian proximal tubules. Taken together, our findings are consistent with a role for Hnf1b as a critical determinant of proximal tubule transport function by acting upstream of a large number of SLC genes and validate the zebrafish as a physiologically relevant model of the mammalian proximal tubule.

GWAS on prolonged gestation (post-term birth): analysis of successive Finnish birth cohorts.

BACKGROUND: Gestation is a crucial timepoint in human development. Deviation from a term gestational age correlates with both acute and long-term adverse health effects for the child. Both being born preterm and post-term, that is, having short and long gestational ages, are heritable and influenced by the prenatal and perinatal environment. Despite the obvious heritable component, specific genetic influences underlying differences in gestational age are poorly understood. METHODS: We investigated the genetic architecture of gestational age in 9141 individuals, including 1167 born post-term, across two Northern Finland cohorts born in 1966 or 1986. RESULTS: Here we identify one globally significant intronic genetic variant within the ADAMTS13 gene that is associated with prolonged gestation (p=4.85×10-8). Additional variants that reached suggestive levels of significance were identified within introns at the ARGHAP42 and TKT genes, and in the upstream (5') intergenic regions of the B3GALT5 and SSBP2 genes. The variants near the ADAMTS13, B3GALT5, SSBP2 and TKT loci are linked to alterations in gene expression levels (cis-eQTLs). Luciferase assays confirmed the allele specific enhancer activity for the BGALT5 and TKT loci. CONCLUSIONS: Our findings provide the first evidence of a specific genetic influence associated with prolonged gestation. This study forms a foundation for a better understanding of the genetic and long-term health risks faced by induced and post-term individuals. The long-term risks for induced individuals who have a previously overlooked post-term potential may be a major issue for current health providers.

Identification of human skeletal muscle miRNA related to strength by high-throughput sequencing.

The loss of muscle size, strength, and quality with aging is a major determinant of morbidity and mortality in the elderly. The regulatory pathways that impact the muscle phenotype include the translational regulation maintained by microRNAs (miRNA). Yet the miRNAs that are expressed in human skeletal muscle and relationship to muscle size, strength, and quality are unknown. Using next-generation sequencing, we selected the 50 most abundantly expressed miRNAs and then analyzed them in vastus lateralis muscle, obtained by biopsy from middle-aged males ( n = 48; 50.0 ± 4.3 yr). Isokinetic strength testing and midthigh computed tomography was undertaken for muscle phenotype analysis. Muscle attenuation was measured by computerized tomography and is inversely proportional to myofiber lipid content. miR-486-5p accounted for 21% of total miR sequence reads, with miR-10b-5p, miR-133a-3p, and miR-22-3p accounting for a further 15, 12, and 10%, respectively. Isokinetic knee extension strength and muscle cross-sectional area were positively correlated with miR-100-5p, miR-99b-5p, and miR-191-5p expression. Muscle attenuation was negatively correlated to let-7f-5p, miR-30d-5p, and miR-125b-5p expression. In silico analysis implicates miRNAs related to strength and muscle size in the regulation of mammalian target of rapamycin, while miRNAs related to muscle attenuation may have potential roles regulating the transforming growth factor-ß/SMAD3 pathway.

Intergenic GWAS SNPs are key components of the spatial and regulatory network for human growth.

Meta-analysis of genome-wide association studies has resulted in the identification of hundreds of genetic variants associated with growth and stature. Determining how these genetic variants influence growth is important, but most are non-coding, and there is little understanding of how these variants contribute to adult height. To determine the mechanisms by which human variation contributes to growth, we combined spatial genomic connectivity (high-throughput conformation capture) with functional (gene expression, expression Quantitative Trait Loci) data to determine how non-genic loci associated with infant length, pubertal and adult height and contribute to gene regulatory networks. This approach identified intergenic single-nucleotide polymorphisms (SNPs) ∼85 kb upstream of FBXW11 that spatially connect with distant loci. These regulatory connections are reinforced by evidence of SNP-enhancer effects and altered expression in genes influencing the action of human growth hormone. Functional assays provided evidence for enhancer activity of the intergenic region near FBXW11 that harbors SNP rs12153391, which is associated with an expression Quantitative Trait Loci. Our results suggest that variants in this locus have genome-wide effects as key modifiers of growth (both overgrowth and short stature) acting through a regulatory network. We believe that the genes and pathways connected with this regulatory network are potential targets that could be investigated for diagnostic, prenatal and carrier testing for growth disorders. Finally, the regulatory networks we generated illustrate the power of using existing datasets to interrogate the contribution of intergenic SNPs to common syndromes/diseases.

Whole-genome analysis informs breast cancer response to aromatase inhibition.

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.

Genome Modeling System: A Knowledge Management Platform for Genomics.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Genome remodelling in a basal-like breast cancer metastasis and xenograft.

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.

MuSiC: identifying mutational significance in cancer genomes.

Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.

SciClone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution.

The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy.

Smooth muscle cells from abdominal aortic aneurysms are unique and can independently and synergistically degrade insoluble elastin.

BACKGROUND: The purpose of this study was to further elucidate the role of the vascular smooth muscle cells (SMCs) in abdominal aortic aneurysm (AAA) disease. We hypothesized that that AAA SMCs are unique and actively participate in the process of degrading the aortic matrix. METHODS: Whole-genome expression profiles of SMCs from AAAs, nondilated abdominal aorta (NAA), and carotid endarterectomy (CEA) were compared. We quantified elastolytic activity by culturing SMCs in [(3)H]elastin-coated plates and measuring solubilized tritium in the media after 7 days. Matrix metalloproteinase (MMP)-2 and MMP-9 production was assessed using real-time polymerase chain reaction, zymography, and Western blotting. RESULTS: Each SMC type exhibited a unique gene expression pattern. AAA SMCs had greater elastolytic activity than NAA-SMCs (+68%; P < .001) and CEA-SMCs (+45%; P < .001). Zymography showed an increase of active MMP-2 (62 kD) in media from AAA SMCs. AAA SMCs demonstrated twofold greater expression of MMP-2 messenger (m)RNA (P < .05) and 7.3-fold greater MMP-9 expression (P < .01) than NAA-SMCs. Culture with U937 monocytes caused a synergistic increase of elastolysis by AAA SMCs (41%; P < .001) but not NAA-SMCs or CEA-SMCs (P = .99). Coculture with U937 caused a large increase in MMP-9 mRNA in AAA-SMCs and NAA-SMCs (P < .001). MMP-2 mRNA expression was not affected. Western blots of culture media showed a fourfold increase of MMP-9 (92 kD) protein only in AAA-SMCs/U937 but not in NAA-SMCs/U937 (P < .001) and a large increase in active-MMP2 (62 kD), which was less apparent in NAA-SMCs/U937 media (P < .01). CONCLUSIONS: AAA-SMCs have a unique gene expression profile and a proelastolytic phenotype that is augmented by macrophages. This may occur by a failure of post-transcriptional control of MMP-9 synthesis.

Links between melanoma germline risk loci, driver genes and comorbidities: insight from a tissue-specific multi-omic analysis.

Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk. This integrative approach revealed a total of 151 target genes, both near and far away from the risk loci in linear sequence, with known and novel roles in the etiology of melanoma. Using protein-protein interaction networks, we identified proteins that interact-directly or indirectly-with the products of the target genes. The interacting proteins were enriched for known melanoma driver genes. Further integration of these target genes into tissue-specific gene regulatory networks revealed patterns of gene regulation that connect melanoma to its comorbidities. Our study provides novel insights into the biological implications of genetic variants associated with melanoma risk.

Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay.

Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.

Resting EEG correlates of neurodevelopment in a socioeconomically and linguistically diverse sample of toddlers: Wave 1 of the Kia Timata Pai best start New Zealand study.

Development of communication and self-regulation skills is fundamental to psychosocial maturation in childhood. The Kia Timata Pai Best Start (KTP) longitudinal study aims to promote these skills through interventions delivered at early childcare centers across New Zealand. In addition to evaluating effects of the interventions on behavioral and cognitive outcomes, the study utilizes electroencephalography (EEG) to characterize cortical development in a subsample of participating children. Here, we present results of the baseline resting EEG assessment with 193 children aged 15 to 33 months. We identified EEG correlates of individual differences in demographics, communication abilities, and temperament. We obtained communication and behavior ratings from multiple informants, and we applied contemporary analytic methods to the EEG data. Periodic spectral power adjusted for aperiodic activity was most closely associated with demographic, language, and behavioral measures. As in previous studies, gamma power was positively associated with verbal language. Alpha power was positively associated with effortful control. Nonverbal and verbal language measures showed distinct associations with EEG indices, as did the three temperament domains. Our results identified a number of candidate EEG measurements for use as longitudinal markers of optimal cortical development and response to interventions in the KTP cohort.