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Biomedical subjects

Roel A Ophoff

Publications and source records attributed to Roel A Ophoff.

16 recordsLinked to original sources

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10 kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

DNA Copy Number Variations↗

Distinct patterns of de novo coding variants contribute to Tourette Syndrome etiology.

Tourette syndrome (TS) is a highly heritable childhood-onset neuropsychiatric disorder characterized by persistent motor and vocal tics. While both common and rare variants contribute to TS susceptibility, the role of rare de novo mutations (DNMs) remains incompletely characterized. Here, we report findings from the largest TS whole-exome sequencing study to date, analyzing 1,466 TS trios alongside 6,714 autism spectrum disorder (ASD) trios and 5,880 unaffected sibling controls from the Simons Simplex Collection (SSC) and SPARK cohorts. Leveraging a trio-based design across these cohorts enabled calibrated assessment of DNM burden while controlling for background mutation rates. We observed a significant exome-wide enrichment of protein-truncating DNMs in TS probands, particularly within genes intolerant to loss-of-function variation (pLI ≥ 0.9), with little contribution from damaging missense variants. Notably, TS probands did not exhibit enrichment in previously implicated ASD or developmental delay (DD) genes, but elsewhere in the genome, suggesting a distinct rare variant architecture. Using a Bayesian statistical framework that integrates both de novo and rare inherited coding variants, we identified three candidate TS risk genes with FDR ≤ 0.05: PPP5C , EXOC1 , and GXYLT1 . Literature shows that they have prior links to neurodevelopmental and psychiatric disorders. These findings reveal a rare variant burden in TS that is genetically distinguishable from ASD, underscore the importance of loss-of-function mutations in TS risk, and nominate novel candidate genes for future functional investigation.

Journal Article↗

A decentralized future for the open-science databases.

The continuous and reliable open access to curated biological data repositories is indispensable for accelerating rigorous scientific inquiry and fostering reproducible research outcomes. However, the current paradigm, which relies heavily on centralized infrastructure for the storage and distribution of foundational biomedical datasets, inherently introduces significant vulnerabilities. This centralized model is susceptible to single points of failure, including cyberattacks, technical malfunctions, natural disasters, and even political or funding uncertainties. Such disruptions can lead to widespread data unavailability, data loss, integrity compromises, and substantial delays in critical research, ultimately impeding scientific progress. The downstream effect of such interruptions can be the widespread paralysis of diverse research activities, including computational, clinical, molecular, and climate studies. This scenario vividly illustrates the inherent dangers of consolidating essential scientific resources within a single geopolitical or institutional locus. As data generation is accelerating and the global landscape continues to fluctuate, the sustainability of centralized models must be critically re-evaluated. A shift toward federated and decentralized architectures may offer a robust and forward-looking approach to enhancing the resilience of scientific data infrastructures by reducing exposure to governance instability, infrastructural fragility, and funding volatility, while also promoting equity and global accessibility. Inspired by established models such as ELIXIR's federated infrastructure and the policy and funding frameworks developed by CODATA and the Global Biodata Coalition (GBC), emerging Decentralized Science (DeSci) initiatives can contribute to building more resilient, fair, and incentive-aligned data ecosystems. The future of open science depends on integrating these complementary approaches to establish a globally distributed, economically sustainable, and institutionally robust infrastructure that safeguards scientific data as a public good, further ensuring continued accessibility, interoperability, and preservation for generations to come. Here, we examine the structural limitations of centralized repositories, evaluate federated and decentralized models, and propose a hybrid framework for resilient, fair, and sustainable scientific data stewardship.

data accessibility↗

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, D MAX and Method, and find an optimal D MAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

Journal Article↗

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Journal Article↗

Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies.

BACKGROUND: DNA methylation (DNAm)-based predictors hold great promise to serve as clinical tools for health interventions and disease management. While these algorithms often have high prediction accuracy, the consistency of their performance remains to be determined. We therefore conduct a systematic evaluation across 101 different DNAm data preprocessing and normalization strategies and assess how each analytical strategy affects the consistency of 41 DNAm-based predictors. RESULTS: Our analyses are conducted in a large EPIC DNAm array dataset from the Jackson Heart Study (N = 2053) that included 146 pairs of technical replicate samples. By estimating the average absolute agreement between replicate pairs, we show that 32 out of 41 predictors (78%) demonstrate excellent consistency when appropriate data processing and normalization steps are implemented. Across all pairs of predictors, we find a moderate correlation in performance across analytical strategies (mean rho = 0.40, SD = 0.27), highlighting significant heterogeneity in performance across algorithms. Successful or unsuccessful removal of technical variation furthermore significantly impacts downstream phenotypic association analysis, such as all-cause mortality risk associations. CONCLUSIONS: We show that DNAm-based algorithms are sensitive to technical variation. The right choice of data processing strategy is important to achieve reproducible estimates and improve prediction accuracy in downstream phenotypic association analyses. For each of the 41 DNAm predictors, we report its degree of consistency and provide the best performing analytical strategy as a guideline for the research community. As DNAm-based predictors become more and more widely used, our work helps improve their performance and standardize their implementation.

DNA Methylation↗

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Brain↗

Common genetic variations in CCK, leptin, and leptin receptor genes are associated with specific human eating patterns.

Obesity has a heritable component; however, the heterogeneity of obesity complicates dissection of its genetic background. In this study, we therefore focused on eating patterns as specific traits within obesity. These traits have a heritable component; genes associated with a specific eating pattern have not yet been reported at the population level. In this study, we determined whether genetic variations in cholecystokinin (CCK) and leptin genes underlie specific eating patterns. We selected obese individuals showing extreme snacking behavior or use of excessive portion sizes from a large population-based sample (n = 17,357) from the Prospect-EPIC (European Prospective Study into Cancer and Nutrition) study. Using allele-specific PCRs, we tested several single nucleotide polymorphisms in the candidate genes and performed haplotype analysis. Obese carriers of common allelic variations in leptin or the leptin receptor gene had an increased risk to display extreme snacking behavior. In contrast, obese carriers of common allelic variations in CCK had an increased risk to eating increased meal sizes. In conclusion, we identified common allelic variants specifically associated with distinctly different eating patterns, namely extreme snacking behavior or excessive portion size.

Aged↗

Analysis of segmental duplications reveals a distinct pattern of continuation-of-synteny between human and mouse genomes.

About 5% of the human genome consists of large-scale duplicated segments of almost identical sequences. Segmental duplications (SDs) have been proposed to be involved in non-allelic homologous recombination leading to recurrent genomic variation and disease. It has also been suggested that these SDs are associated with syntenic rearrangements that have shaped the human genome. We have analyzed 14 members of a single family of closely related SDs in the human genome, some of which are associated with common inversion polymorphisms at chromosomes 8p23 and 4p16. Comparative analysis with the mouse genome revealed syntenic inversions for these two human polymorphic loci. In addition, 12 of the 14 SDs, while absent in the mouse genome, occur at the breaks of synteny; suggesting a non-random involvement of these sequences in genome evolution. Furthermore, we observed a syntenic familial relationship between 8 and 12 breakpoint-loci, where broken synteny that ends at one family member resumes at another, even across different chromosomes. Subsequent genome-wide assessment revealed that this relationship, which we named continuation-of-synteny, is not limited to the 8p23 family and occurs 46 times in the human genome with high frequency at specific chromosomes. Our analysis supports a non-random breakage model of genomic evolution with an active involvement of segmental duplications for specific regions of the human genome.

Animals↗

Accommodating chromosome inversions in linkage analysis.

This work develops a population-genetics model for polymorphic chromosome inversions. The model precisely describes how an inversion changes the nature of and approach to linkage equilibrium. The work also describes algorithms and software for allele-frequency estimation and linkage analysis in the presence of an inversion. The linkage algorithms implemented in the software package Mendel estimate recombination parameters and calculate the posterior probability that each pedigree member carries the inversion. Application of Mendel to eight Centre d'Etude du Polymorphisme Humain pedigrees in a region containing a common inversion on 8p23 illustrates its potential for providing more-precise estimates of the location of an unmapped marker or trait gene. Our expanded cytogenetic analysis of these families further identifies inversion carriers and increases the evidence of linkage.

Algorithms↗

Chromosome 19p13 loci in Finnish migraine with aura families.

Chromosomal area 19p13 contains two migraine associated genes: a Ca(v)2.1 (P/Q-type) calcium channel alpha(1) subunit gene, CACNA1A, and an insulin receptor gene, INSR. Missense mutations in CACNA1A cause a rare Mendelian form of migraine, familial hemiplegic migraine type 1 (FHM1). Contribution of CACNA1A locus has also been studied in the common forms of migraine, migraine with (MA) and without aura (MO), but the results have been contradictory. The role of INSR is less well established: A region on 19p13 separate from CACNA1A was recently reported to be a major locus for migraine and subsequently, the INSR gene was associated with MA and MO. Our aim was to clarify the role of these loci in MA families by analyzing 72 multigenerational Finnish MA families, the largest family sample so far. We hypothesized that the potential major contribution of the 19p13 loci should be detected in a family sample of this size, and this was confirmed by simulations. We genotyped eight polymorphic microsatellite markers surrounding the INSR and CACNA1A genes on 757 individuals. Using parametric and non-parametric linkage analysis, none of the studied markers showed any evidence of linkage to MA either under locus homogeneity or heterogeneity. However, marginally positive lod scores were observed in three families, and thus for these families the results remain inconclusive. The overall conclusion is that our study did not provide evidence of a major MA susceptibility region on 19p13 and thus we were not able to replicate the INSR locus finding.

Antigens, CD↗

Genetic contributions to social impulsivity and aggressiveness in vervet monkeys.

BACKGROUND: Impulsivity contributes to multiple psychiatric disorders and sociobehavioral problems, and the more serious consequences of impulsivity are typically manifest in social situations. This study assessed the genetic contribution to impulsivity and aggressiveness in a social context using a nonhuman primate model. METHODS: Subjects were 352 adolescent and adult vervet monkeys from an extended multigenerational pedigree. Behavior was assessed in the Intruder Challenge Test, a standardized test that measures impulsivity and aggressiveness toward a stranger. Genetic and maternal contributions to variation in the Social Impulsivity Index and its two subscales, impulsive approach and aggression, were estimated using variance components analyses. RESULTS: The results found significant genetic contributions to social impulsivity (h2 =.35 +/-.11) and to each of the subscales, with no significant influence of maternal environment. There was a high genetic correlation between the impulsive approach and aggression subscales (rho =.78 +/-.12). CONCLUSIONS: This is the first study to demonstrate heritability of social impulsivity in adolescents and adults for any nonhuman primate species. The high genetic correlation suggests the same genes may influence variation in both impulsive approach and aggression. These results provide a promising basis for identification of susceptibility loci for impulsivity and aggressiveness.

Age Factors↗

Genetic studies of neuropsychiatric disorders in Costa Rica: a model for the use of isolated populations.

The importance of genetics in understanding the etiology of mental illness has become increasingly clear in recent years, as more evidence has mounted that almost all neuropsychiatric disorders have a genetic component. It has also become clear, however, that these disorders are etiologically complex, and multiple genetic and environmental factors contribute to their makeup. So far, traditional linkage mapping studies have not definitively identified specific disease genes for neuropsychiatric disorders, although some potential candidates have been identified via these methods (e.g. the dysbindin gene in schizophrenia; Straub et al., 2002; Schwab et al., 2003). For this reason, alternative approaches are being attempted, including studies in genetically isolated populations. Because isolated populations have a high degree of genetic homogeneity, their use may simplify the process of identifying disease genes in disorders where multiple genes may play a role. Several areas of Latin America contain genetically isolated populations that are well suited for the study of neuropsychiatric disorders. Genetic studies of several major psychiatric illnesses, including bipolar disorder, major depression, schizophrenia, Tourette Syndrome, alcohol dependence, attention deficit hyperactivity disorder, and obsessive-compulsive disorder, are currently underway in these regions. In this paper we highlight the studies currently being conducted by our groups in the Central Valley of Costa Rica to illustrate the potential advantages of this population for genetic studies.

Attitude to Health↗

A genome-wide survey of segmental duplications that mediate common human genetic variation of chromosomal architecture.

Recent studies have identified a small number of genomic rearrangements that occur frequently in the general population. Bioinformatics tools are now available for systematic genome-wide surveys of higher-order structures predisposing to such common variations in genomic architecture. Segmental duplications (SDs) constitute up to 5 per cent of the genome and play an important role in generating additional rearrangements and in disease aetiology. We conducted a genome-wide database search for a form of SD, palindromic segmental duplications (PSDs), which consist of paired, inverted duplications, and which predispose to inversions, duplications and deletions. The survey was complemented by a search for SDs in tandem orientation (TSDs) that can mediate duplications and deletions but not inversions. We found more than 230 distinct loci with higher-order genomic structure that can mediate genomic variation, of these about 180 contained a PSD. A number of these sites were previously identified as harbouring common inversions or as being associated with specific genomic diseases characterised by duplication, deletions or inversions. Most of the regions, however, were previously unidentified; their characterisation should identify further common rearrangements and may indicate localisations for additional genomic disorders. The widespread distribution of complex chromosomal architecture suggests a potentially high degree of plasticity of the human genome and could uncover another level of genetic variation within human populations.

Chromosomes, Human↗

Genomewide linkage disequilibrium mapping of severe bipolar disorder in a population isolate.

Genomewide association studies may offer the best promise for genetic mapping of complex traits. Such studies in outbred populations require very densely spaced single-nucleotide polymorphisms. In recently founded population isolates, however, extensive linkage disequilibrium (LD) may make these studies feasible with currently available sets of short tandem repeat markers, spaced at intervals as large as a few centimorgans. We report the results of a genomewide association study of severe bipolar disorder (BP-I), using patients from the isolated population of the central valley of Costa Rica. We observed LD with BP-I on several chromosomes; the most striking results were in proximal 8p, a region that has previously shown linkage to schizophrenia. This region could be important for severe psychiatric disorders, rather than for a specific phenotype.

Bipolar Disorder↗