Janet Harwood

Dr. Janet Harwood

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Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 April 2022 in Nature Genetics
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Journal Article
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CBCéline Bellenguez
Céline Bellenguez
FKFahri Küçükali
Fahri Küçükali
IJIris E. Jansen
Iris E. Jansen
LKLuca Kleineidam
Luca Kleineidam
SMSonia Moreno-Grau
Sonia Moreno-Grau
JLJean-Charles Lambert
Jean-Charles Lambert
Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

1 April 2021 in Brain Communications
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JHJanet Harwood
Janet Harwood
GLGanna Leonenko
Ganna Leonenko
RSRebecca Sims
Rebecca Sims
VEValentina Escott-Price
Valentina Escott-Price
JWJulie Williams
Julie Williams
PHPeter Holmans
Peter Holmans
Defining the mechanisms involved in the aetiology of Alzheimer’s disease from genome-wide association studies alone is challenging since Alzheimer’s disease is polygenic and most genetic variants are non-coding. Non-coding Alzheimer’s disease risk variants can influence gene expression by affecting miRNA binding and those located within enhancers and within CTCF sites may influence gene expression through alterations in chromatin states. In addition, their function can be cell-type specific. They can function specifically in microglial enhancers thus affecting gene expression in the brain. Hence, transcriptome-wide association studies have been applied to test the genetic association between disease risk and cell-/tissue-specific gene expression. Many Alzheimer’s disease-associated loci are involved in the pathways of the innate immune system. Both microglia, the primary immune cells of the brain, and monocytes which can infiltrate the brain and differentiate into activated macrophages, have roles in neuroinflammation and β‐amyloid clearance through phagocytosis. In monocytes the function of regulatory variants can be context-specific after immune stimulation. To dissect the variants associated with Alzheimer’s disease in the context of monocytes, we utilized data from naïve monocytes and following immune stimulation in vitro, in combination with genome-wide association studies of Alzheimer’s disease in transcriptome-wide association studies. Of the nine genes with statistically independent transcriptome-wide association signals, seven are located in known Alzheimer’s disease risk loci: BIN1, PTK2B, SPI1, MS4A4A, MS4A6E, APOE and PVR. The transcriptome-wide association signal for MS4A6E, PTK2B and PVR and the direction of effect replicated in an independent genome-wide association studies. Our analysis identified two novel candidate genes for Alzheimer’s disease risk, LACTB2 and PLIN2/ADRP. LACTB2 replicated in a transcriptome-wide association study using independent expression weights. LACTB2 and PLIN2/ADRP are involved in mitochondrial function and lipid metabolism, respectively. Comparison of transcriptome-wide association study results from monocytes, whole blood and brain showed that the signal for PTK2B is specific to blood and MS4A6E is specific to LPS stimulated monocytes.

20 March 2021 in Genes
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SCSarah Carpanini
Sarah Carpanini
JHJanet Harwood
Janet Harwood
EBEmily Baker
Emily Baker
MTMegan Torvell
Megan Torvell
TCThe GERAD1 Consortium
The GERAD1 Consortium
BMB Paul Morgan
B Paul Morgan
Late-onset Alzheimer’s disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies (GWAS) have identified over seventy novel genetic susceptibility loci for LOAD. Most are implicated in microglial or inflammatory pathways, bringing inflammation to the fore as a candidate pathological pathway. Among the most significant GWAS hits are three complement genes: CLU, encoding the fluid-phase complement inhibitor clusterin; CR1 encoding complement receptor 1 (CR1); and recently, C1S encoding the complement enzyme C1s. Complement activation is a critical driver of inflammation; changes in complement genes may impact risk by altering the inflammatory status in the brain. To assess complement gene association with LOAD risk, we manually created a comprehensive complement gene list and tested these in gene-set analysis with LOAD summary statistics. We confirmed associations of CLU and CR1 genes with LOAD but showed no significant associations for the complement gene-set when excluding CLU and CR1. No significant association with other complement genes, including C1S, was seen in the IGAP dataset; however, these may emerge from larger datasets.

1 September 2021 in Biological Psychiatry
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NCNicholas Clifton
Nicholas Clifton
LCLeonardo Collado-Torres
Leonardo Collado-Torres
EBEmily E. Burke
Emily E. Burke
APAntonio F. Pardiñas
Antonio F. Pardiñas
JHJanet Harwood
Janet Harwood
JHJeremy Hall
Jeremy Hall
Recent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant. We aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used postmortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple prenatal and postnatal time points, with summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder, and major depressive disorder. We prioritized gene sets for overall enrichment of association with each disorder and then tested the relationship between the association of their constituent genes with their relative expression at each developmental stage. We observed relationships between the expression of genes involved in voltage-gated cation channel activity during early midfetal, adolescence, and early adulthood time points and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during early midfetal development and higher expression during adolescence and early adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, while for bipolar disorder, the relationship was distributed between calcium and potassium channel activity genes. Our results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk for psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

9 January 2025 in Brain
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Journal Article
Open access
AGAndrew C Graham
Andrew C Graham
EBEftychia Bellou
Eftychia Bellou
JHJanet Harwood
Janet Harwood
UYUmran Yaman
Umran Yaman
MCMeral Celikag
Meral Celikag
DSDervis A Salih
Dervis A Salih
Ageing underlies functional decline of the brain and is the primary risk factor for several neurodegenerative conditions, including Alzheimer’s disease (AD). However, the molecular mechanisms that cause functional decline of the brain during ageing, and how these contribute to AD pathogenesis, are not well understood. The objective of this study was to identify biological processes that are altered during ageing in the hippocampus and that modify Ad risk and lifespan, and then to identify putative gene drivers of these programmes. We integrated common human genetic variation associated with human lifespan or Ad from genome-wide association studies with co-expression transcriptome networks altered with age in the mouse and human hippocampus. Our work confirmed that genetic variation associated with Ad was enriched in gene networks expressed by microglia responding to ageing and revealed that they were also enriched in an oligodendrocytic gene network. Compellingly, longevity-associated genetic variation was enriched in a gene network expressed by homeostatic microglia whose expression declined with age. The genes driving this enrichment include CASP8 and STAT3, highlighting a potential role for these longevity-associated genes in the homeostatic functions of innate immune cells, and these genes might drive ‘inflammageing’. Thus, we observed that gene variants contributing to ageing and AD balance different aspects of microglial and oligodendrocytic function. Furthermore, we also highlight putative Ad risk genes, such as LAPTM5, ITGAM and LILRB4, whose association with Ad falls below genome-wide significance but show strong co-expression with known Ad risk genes in these networks. Indeed, five of the putative risk genes highlighted by our analysis, ANKH, GRN, PLEKHA1, SNX1 and UNC5CL, have subsequently been identified as genome-wide significant risk genes in a subsequent genome-wide association study with larger sample size, validating our analysis. This work identifies new genes that influence ageing and AD pathogenesis, and highlights the importance of microglia and oligodendrocytes in the resilience of the brain against ageing and AD pathogenesis. Our findings have implications for developing markers indicating the physiological age of the brain and new targets for therapeutic intervention.

24 July 2024 in Molecular Psychiatry
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RGRuben Gur
Ruben Gur
CBCarrie E. Bearden
Carrie E. Bearden
SJSebastien Jacquemont
Sebastien Jacquemont
ASAnn Swillen
Ann Swillen
TATherese van Amelsvoort
Therese van Amelsvoort
RGRaquel E. Gur
Raquel E. Gur
Rare recurrent copy number variants (CNVs) at chromosomal loci 22q11.2 and 16p11.2 are genetic disorders with lifespan risk for neuropsychiatric disorders. Microdeletions and duplications are associated with neurocognitive deficits, yet few studies compared these groups using the same measures to address confounding measurement differences. We report a prospective international collaboration applying the same computerized neurocognitive assessment, the Penn Computerized Neurocognitive Battery (CNB), administered in a multi-site study on rare genomic disorders: 22q11.2 deletions (n = 492); 22q11.2 duplications (n = 106); 16p11.2 deletion (n = 117); and 16p11.2 duplications (n = 46). Domains examined include executive functions, episodic memory, complex cognition, social cognition, and psychomotor speed. Accuracy and speed for each domain were included as dependent measures in a mixed-model repeated measures analysis. Locus (22q11.2, 16p11.2) and Copy number (deletion/duplication) were grouping factors and Measure (accuracy, speed) and neurocognitive domain were repeated measures factors, with Sex and Site as covariates. We also examined correlation with IQ. We found a significant Locus × Copy number × Domain × Measure interaction (p = 0.0004). 22q11.2 deletions were associated with greater performance accuracy deficits than 22q11.2 duplications, while 16p11.2 duplications were associated with greater specific deficits than 16p11.2 deletions. Duplications at both loci were associated with reduced speed compared to deletions. Performance profiles differed among the groups with particularly poor memory performance of the 22q11.2 deletion group while the 16p11.2 duplication group had greatest deficits in complex cognition. Average accuracy on the CNB was moderately correlated with Full Scale IQ. Deletions and duplications of 22q11.2 and 16p11.2 have differential effects on accuracy and speed of neurocognition indicating locus specificity of performance profiles. These profile differences can help inform mechanistic substrates to heterogeneity in presentation and outcome, and can only be established in large-scale international consortia using the same neurocognitive assessment. Future studies could aim to link performance profiles to clinical features and brain function.