The effects of genotype on inflammatory response in hippocampal progenitor cells: A computational approach.

Cell culture models are valuable tools to study biological mechanisms underlying health and disease in a controlled environment. Although their genotype influences their phenotype, subtle genetic variations in cell lines are rarely characterised and taken into account for in vitro studies. To investigate how the genetic makeup of a cell line might affect the cellular response to inflammation, we characterised the single nucleotide variants (SNPs) relevant to inflammation-related genes in an established hippocampal progenitor cell line (HPC0A07/03C) that is frequently used as an in vitro model for hippocampal neurogenesis (HN). SNPs were identified using a genotyping array, and genes associated with chronic inflammatory and neuroinflammatory response gene ontology terms were retrieved using the AmiGO application. SNPs associated with these genes were then extracted from the genotyping dataset, for which a literature search was conducted, yielding relevant research articles for a total of 17 SNPs. Of these variants, 10 were found to potentially affect hippocampal neurogenesis whereby a majority (n=7) is likely to reduce neurogenesis under inflammatory conditions. Taken together, the existing literature seems to suggest that all stages of hippocampal neurogenesis could be negatively affected due to the genetic makeup in HPC0A07/03C cells under inflammation. Additional experiments will be needed to validate these specific findings in a laboratory setting. However, this computational approach already confirms that in vitro studies in general should control for cell lines subtle genetic variations which could mask or exacerbate findings.

A recessive S174X mutation in Optineurin causes amyotrophic lateral sclerosis through a loss of function via allele-specific nonsense-mediated decay.

Loss of function (LoF) mutations in Optineurin can cause recessive amyotrophic lateral sclerosis (ALS) with some heterozygous LoF mutations associated with dominant ALS. The molecular mechanisms underlying the variable inheritance pattern associated with OPTN mutations have remained elusive. We identified that affected members of a consanguineous Middle Eastern ALS kindred possessed a novel homozygous p.S174X OPTN mutation. Analysis of these primary fibroblast lines from family members identified that the p.S174X mutation reduces OPTN mRNA expression in an allele-dependent fashion by nonsense mediated decay. Western blotting correlated a reduced expression in heterozygote carriers but a complete absence of OPTN protein in the homozygous carrier. This data suggests that the p.S174X truncation mutation causes recessive ALS through LoF. However, functional analysis detected a significant increase in mitophagy markers TOM20 and COXIV, and higher rates of mitochondrial respiration and ATP levels in heterozygous carriers only. This suggests that heterozygous LoF OPTN mutations may not be causative in a Mendelian manner but may potentially behave as contributory ALS risk factors.

Genome-wide Meta-analysis Finds the ACSL5-ZDHHC6 Locus Is Associated with ALS and Links Weight Loss to the Disease Genetics.

We meta-analyze amyotrophic lateral sclerosis (ALS) genome-wide association study (GWAS) data of European and Chinese populations (84,694 individuals). We find an additional significant association between rs58854276 spanning ACSL5-ZDHHC6 with ALS (p = 8.3 × 10-9), with replication in an independent Australian cohort (1,502 individuals; p = 0.037). Moreover, B4GALNT1, G2E3-SCFD1, and TRIP11-ATXN3 are identified using a gene-based analysis. ACSL5 has been associated with rapid weight loss, as has another ALS-associated gene, GPX3. Weight loss is frequent in ALS patients and is associated with shorter survival. We investigate the effect of the ACSL5 and GPX3 single-nucleotide polymorphisms (SNPs), using longitudinal body composition and weight data of 77 patients and 77 controls. In patients' fat-free mass, although not significant, we observe an effect in the expected direction (rs58854276: -2.1 ± 1.3 kg/A allele, p = 0.053; rs3828599: -1.0 ± 1.3 kg/A allele, p = 0.22). No effect was observed in controls. Our findings support the increasing interest in lipid metabolism in ALS and link the disease genetics to weight loss in patients.

An epigenome-wide association study of Alzheimer's disease blood highlights robust DNA hypermethylation in the HOXB6 gene.

A growing number of epigenome-wide association studies have demonstrated a role for DNA methylation in the brain in Alzheimer's disease. With the aim of exploring peripheral biomarker potential, we have examined DNA methylation patterns in whole blood collected from 284 individuals in the AddNeuroMed study, which included 89 nondemented controls, 86 patients with Alzheimer's disease, and 109 individuals with mild cognitive impairment, including 38 individuals who progressed to Alzheimer's disease within 1 year. We identified significant differentially methylated regions, including 12 adjacent hypermethylated probes in the HOXB6 gene in Alzheimer's disease, which we validated using pyrosequencing. Using weighted gene correlation network analysis, we identified comethylated modules of genes that were associated with key variables such as APOE genotype and diagnosis. In summary, this study represents the first large-scale epigenome-wide association study of Alzheimer's disease and mild cognitive impairment using blood. We highlight the differences in various loci and pathways in early disease, suggesting that these patterns relate to cognitive decline at an early stage.

Genome-wide association study of rate of cognitive decline in Alzheimer's disease patients identifies novel genes and pathways.

INTRODUCTION: Variability exists in the disease trajectories of Alzheimer's disease (AD) patients. We performed a genome-wide association study to examine rate of cognitive decline (ROD) in patients with AD. METHODS: We tested for interactions between genetic variants and time since diagnosis to predict the ROD of a composite cognitive score in 3946 AD cases and performed pathway analysis on the top genes. RESULTS: Suggestive associations (P < 1.0 × 10-6 ) were observed on chromosome 15 in DNA polymerase-γ (rs3176205, P = 1.11 × 10-7 ), chromosome 7 (rs60465337,P = 4.06 × 10-7 ) in contactin-associated protein-2, in RP11-384F7.1 on chromosome 3 (rs28853947, P = 5.93 × 10-7 ), family with sequence similarity 214 member-A on chromosome 15 (rs2899492, P = 5.94 × 10-7 ), and intergenic regions on chromosomes 16 (rs4949142, P = 4.02 × 10-7 ) and 4 (rs1304013, P = 7.73 × 10-7 ). Significant pathways involving neuronal development and function, apoptosis, memory, and inflammation were identified. DISCUSSION: Pathways related to AD, intelligence, and neurological function determine AD progression, while previously identified AD risk variants, including the apolipoprotein (APOE) ε4 and ε2 variants, do not have a major impact.

Working Towards a Blood-Derived Gene Expression Biomarker Specific for Alzheimer's Disease.

BACKGROUND: The typical approach to identify blood-derived gene expression signatures as a biomarker for Alzheimer's disease (AD) have relied on training classification models using AD and healthy controls only. This may inadvertently result in the identification of markers for general illness rather than being disease-specific. OBJECTIVE: Investigate whether incorporating additional related disorders in the classification model development process can lead to the discovery of an AD-specific gene expression signature. METHODS: Two types of XGBoost classification models were developed. The first used 160 AD and 127 healthy controls and the second used the same 160 AD with 6,318 upsampled mixed controls consisting of Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, bipolar disorder, schizophrenia, coronary artery disease, rheumatoid arthritis, chronic obstructive pulmonary disease, and cognitively healthy subjects. Both classification models were evaluated in an independent cohort consisting of 127 AD and 687 mixed controls. RESULTS: The AD versus healthy control models resulted in an average 48.7% sensitivity (95% CI = 34.7-64.6), 41.9% specificity (95% CI = 26.8-54.3), 13.6% PPV (95% CI = 9.9-18.5), and 81.1% NPV (95% CI = 73.3-87.7). In contrast, the mixed control models resulted in an average of 40.8% sensitivity (95% CI = 27.5-52.0), 95.3% specificity (95% CI = 93.3-97.1), 61.4% PPV (95% CI = 53.8-69.6), and 89.7% NPV (95% CI = 87.8-91.4). CONCLUSIONS: This early work demonstrates the value of incorporating additional related disorders into the classification model developmental process, which can result in models with improved ability to distinguish AD from a heterogeneous aging population. However, further improvement to the sensitivity of the test is still required.

Genetic associations with radiological damage in rheumatoid arthritis: Meta-analysis of seven genome-wide association studies of 2,775 cases.

BACKGROUND: Previous studies of radiological damage in rheumatoid arthritis (RA) have used candidate-gene approaches, or evaluated single genome-wide association studies (GWAS). We undertook the first meta-analysis of GWAS of RA radiological damage to: (1) identify novel genetic loci for this trait; and (2) test previously validated variants. METHODS: Seven GWAS (2,775 RA cases, of a range of ancestries) were combined in a meta-analysis. Radiological damage was assessed using modified Larsen scores, Sharp van Der Heijde scores, and erosive status. Single nucleotide polymophsim (SNP) associations with radiological damage were tested at a single time-point using regression models. Primary analyses included age and disease duration as covariates. Secondary analyses also included rheumatoid factor (RF). Meta-analyses were undertaken in trans-ethnic and European-only cases. RESULTS: In the trans-ethnic primary meta-analysis, one SNP (rs112112734) in close proximity to HLA-DRB1, and strong linkage disequilibrium with the shared-epitope, attained genome-wide significance (P = 4.2x10-8). In the secondary analysis (adjusting for RF) the association was less significant (P = 1.7x10-6). In both trans-ethnic primary and secondary meta-analyses 14 regions contained SNPs with associations reaching P<5x10-6; in the European primary and secondary analyses 13 and 10 regions contained SNPs reaching P<5x10-6, respectively. Of the previously validated SNPs for radiological progression, only rs660895 (tagging HLA-DRB1*04:01) attained significance (P = 1.6x10-5) and had a consistent direction of effect across GWAS. CONCLUSIONS: Our meta-analysis confirms the known association between the HLA-DRB1 shared epitope and RA radiological damage. The lack of replication of previously validated non-HLA markers highlights a requirement for further research to deliver clinically-useful prognostic genetic markers.

C9orf72 intermediate expansions of 24-30 repeats are associated with ALS.

The expansion of a hexanucleotide repeat GGGGCC in C9orf72 is the most common known cause of ALS accounting for ~ 40% familial cases and ~ 7% sporadic cases in the European population. In most people, the repeat length is 2, but in people with ALS, hundreds to thousands of repeats may be observed. A small proportion of people have an intermediate expansion, of the order of 20 to 30 repeats in size, and it remains unknown whether intermediate expansions confer risk of ALS in the same way that massive expansions do. We investigated the association of this intermediate repeat with ALS by performing a meta-analysis of four previously published studies and a new British/Alzheimer's Disease Neuroimaging Initiative dataset of 1295 cases and 613 controls. The final dataset comprised 5071 cases and 3747 controls. Our meta-analysis showed association between ALS and intermediate C9orf72 repeats of 24 to 30 repeats in size (random-effects model OR = 4.2, 95% CI = 1.23-14.35, p-value = 0.02). Furthermore, we showed a different frequency of the repeat between the northern and southern European populations (Fisher's exact test p-value = 5 × 10- 3). Our findings provide evidence for the association between intermediate repeats and ALS (p-value = 2 × 10- 4) with direct relevance for research and clinical practice by showing that an expansion of 24 or more repeats should be considered pathogenic.

Transcriptomic analysis of probable asymptomatic and symptomatic alzheimer brains.

Individuals with intact cognition and neuropathology consistent with Alzheimer's disease (AD) are referred to as asymptomatic AD (AsymAD). These individuals are highly likely to develop AD, yet transcriptomic changes in the brain which might reveal mechanisms for their AD vulnerability are currently unknown. Entorhinal cortex, frontal cortex, temporal cortex and cerebellum tissue from 27 control, 33 AsymAD and 52 AD human brains were microarray expression profiled. Differential expression analysis identified a significant increase of transcriptomic activity in the frontal cortex of AsymAD subjects, suggesting fundamental changes in AD may initially begin within the frontal cortex region prior to AD diagnosis. Co-expression analysis identified an overactivation of the brain "glutamate-glutamine cycle", and disturbances in the brain energy pathways in both AsymAD and AD subjects, while the connectivity of key hub genes in this network indicates a shift from an already increased cell proliferation in AsymAD subjects to stress response and removal of amyloidogenic proteins in AD subjects. This study provides new insight into the earliest biological changes occurring in the brain prior to the manifestation of clinical AD symptoms and provides new potential therapeutic targets for early disease intervention.

Differential gene expression analysis in blood of first episode psychosis patients.

BACKGROUND: Psychosis is a condition influenced by an interaction of environmental and genetic factors. Gene expression studies can capture these interactions; however, studies are usually performed in patients who are in remission. This study uses blood of first episode psychosis patients, in order to characterise deregulated pathways associated with psychosis symptom dimensions. METHODS: Peripheral blood from 149 healthy controls and 131 first episode psychosis patients was profiled using Illumina HT-12 microarrays. A case/control differential expression analysis was performed, followed by correlation of gene expression with positive and negative syndrome scale (PANSS) scores. Enrichment analyses were performed on the associated gene lists. We test for pathway differences between first episode psychosis patients who qualify for a Schizophrenia diagnosis against those who do not. RESULTS: A total of 978 genes were differentially expressed and enriched for pathways associated to immune function and the mitochondria. Using PANSS scores we found that positive symptom severity was correlated with immune function, while negative symptoms correlated with mitochondrial pathways. CONCLUSIONS: Our results identified gene expression changes correlated with symptom severity and showed that key pathways are modulated by positive and negative symptom dimensions.

A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data.

BACKGROUND: Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations. OBJECTIVE: Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains. METHODS: Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction. RESULTS: Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the "metabolism of proteins" and viral components were significantly enriched across AD brains. CONCLUSION: This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets.

ALSgeneScanner: a pipeline for the analysis and interpretation of DNA sequencing data of ALS patients.

Amyotrophic lateral sclerosis (ALS, MND) is a neurodegenerative disease of upper and lower motor neurons resulting in death from neuromuscular respiratory failure, typically within two years of first symptoms. Genetic factors are an important cause of ALS, with variants in more than 25 genes having strong evidence, and weaker evidence available for variants in more than 120 genes. With the increasing availability of next-generation sequencing data, non-specialists, including health care professionals and patients, are obtaining their genomic information without a corresponding ability to analyze and interpret it. Furthermore, the relevance of novel or existing variants in ALS genes is not always apparent. Here we present ALSgeneScanner, a tool that is easy to install and use, able to provide an automatic, detailed, annotated report, on a list of ALS genes from whole-genome sequencing (WGS) data in a few hours and whole exome sequence data in about 1 h on a readily available mid-range computer. This will be of value to non-specialists and aid in the interpretation of the relevance of novel and existing variants identified in DNA sequencing data.

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder.

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.

Polygenic risk score analyses of symptoms and treatment response in an antipsychotic-naive first episode of psychosis cohort.

In this study, we aimed to test if the schizophrenia (SCZ) polygenic risk score (PRS) was associated with clinical symptoms in (a) the first episode of psychosis pre-treatment (FEP), (b) at nine weeks after initiation of risperidone treatment (FEP-9W) and (c) with the response to risperidone. We performed a detailed clinical assessment of 60 FEP patients who were antipsychotic-naive and, again, after nine weeks of standardized treatment with risperidone. After blood collection and DNA isolation, the samples were genotyped using the Illumina PsychArrayChip and then imputed. To calculate PRS, we used the latest available GWAS summary statistics from the Psychiatric Genomics Consortium wave-2 SCZ group as a training set. We used Poisson regression to test association between PRS and clinical measurements correcting for the four principal components (genotyping). We considered a p-value < 0.0014 (Bonferroni correction) as significant. First, we verified that the schizophrenia PRS was also able to distinguish cases from controls in this south-eastern Brazilian sample, with a similar variance explained to that seen in Northern European populations. In addition, within-cases analyses, we found that PRS is significantly correlated with baseline (pre-treatment) symptoms, as measured by lower clinical global assessment of functioning (-GAF), higher depressive symptoms and higher scores on a derived excitement factor. After standardized treatment for nine weeks, the correlation with GAF and the excitement factor disappeared while depressive symptoms became negatively associated with PRS. We conclude that drug (and other treatments) may confound attempts to understand the aetiological influence on symptomatology of polygenic risk scores. These results highlight the importance of studying schizophrenia, and other disorders, pre-treatment to understand the relationship between polygenic risk and phenotypic features.

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies.

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2-4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19-0.66) and higher remission rates (OR = 1.55, CI = 1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08-1.47), neurological (OR = 1.28, CI = 1.07-1.53) and sexual side effects (OR = 1.52, CI = 1.23-1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%).

Loss of Trem2 in microglia leads to widespread disruption of cell coexpression networks in mouse brain.

Rare heterozygous coding variants in the triggering receptor expressed in myeloid cells 2 (TREM2) gene, conferring increased risk of developing late-onset Alzheimer's disease, have been identified. We examined the transcriptional consequences of the loss of Trem2 in mouse brain to better understand its role in disease using differential expression and coexpression network analysis of Trem2 knockout and wild-type mice. We generated RNA-Seq data from cortex and hippocampus sampled at 4 and 8 months. Using brain cell-type markers and ontology enrichment, we found subnetworks with cell type and/or functional identity. We primarily discovered changes in an endothelial gene-enriched subnetwork at 4 months, including a shift toward a more central role for the amyloid precursor protein gene, coupled with widespread disruption of other cell-type subnetworks, including a subnetwork with neuronal identity. We reveal an unexpected potential role of Trem2 in the homeostasis of endothelial cells that goes beyond its known functions as a microglial receptor and signaling hub, suggesting an underlying link between immune response and vascular disease in dementia.

Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer.

Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers-either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions. Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array. Firstly, we performed SNP and gene-level analyses of protein-altering variants on the array to identify novel associations the following ADRs, which were grouped into four phenotypes based on symptoms of diarrhea, mucositis, and neutropenia and hand-and-foot syndrome. Secondly, we performed detailed analyses of the HLA region on the same phenotypes after imputing the HLA alleles and amino acids. No protein-altering variants, or sets of protein-altering variants collapsed into genes, were associated with the main outcomes after Bonferroni correction. We found evidence that the HLA region was enriched for associations with Hand-and-Foot syndrome (p = 0.023), but no specific SNPs or HLA alleles were significant after Bonferroni correction. Larger studies will be required to characterize the genetic contribution to ADRs to 5FU. Future studies that focus on the HLA region are likely to be fruitful.

Identification of new risk factors for rolandic epilepsy: CNV at Xp22.31 and alterations at cholinergic synapses.

BACKGROUND: Rolandic epilepsy (RE) is the most common genetic childhood epilepsy, consisting of focal, nocturnal seizures and frequent neurodevelopmental impairments in speech, language, literacy and attention. A complex genetic aetiology is presumed in most, with monogenic mutations in GRIN2A accounting for >5% of cases. OBJECTIVE: To identify rare, causal CNV in patients with RE. METHODS: We used high-density SNP arrays to analyse the presence of rare CNVs in 186 patients with RE from the UK, the USA, Sardinia, Argentina and Kerala, India. RESULTS: We identified 84 patients with one or more rare CNVs, and, within this group, 14 (7.5%) with recurrent risk factor CNVs and 15 (8.0%) with likely pathogenic CNVs. Nine patients carried recurrent hotspot CNVs including at 16p13.11 and 1p36, with the most striking finding that four individuals (three from Sardinia) carried a duplication, and one a deletion, at Xp22.31. Five patients with RE carried a rare CNV that disrupted genes associated with other epilepsies (KCTD7, ARHGEF15, CACNA2D1, GRIN2A and ARHGEF4), and 17 cases carried CNVs that disrupted genes associated with other neurological conditions or that are involved in neuronal signalling/development. Network analysis of disrupted genes with high brain expression identified significant enrichment in pathways of the cholinergic synapse, guanine-exchange factor activation and the mammalian target of rapamycin. CONCLUSION: Our results provide a CNV profile of an ethnically diverse cohort of patients with RE, uncovering new areas of research focus, and emphasise the importance of studying non-western European populations in oligogenic disorders to uncover a full picture of risk variation.

g(HbF): a genetic model of fetal hemoglobin in sickle cell disease.

Fetal hemoglobin (HbF) is a strong modifier of sickle cell disease (SCD) severity and is associated with 3 common genetic loci. Quantifying the genetic effects of the 3 loci would specifically address the benefits of HbF increases in patients. Here, we have applied statistical methods using the most representative variants: rs1427407 and rs6545816 in BCL11A, rs66650371 (3-bp deletion) and rs9376090 in HMIP-2A, rs9494142 and rs9494145 in HMIP-2B, and rs7482144 (Xmn1-HBG2 in the ß-globin locus) to create g(HbF), a genetic quantitative variable for HbF in SCD. Only patients aged ≥5 years with complete genotype and HbF data were studied. Five hundred eighty-one patients with hemoglobin SS (HbSS) or HbSß0 thalassemia formed the "discovery" cohort. Multiple linear regression modeling rationalized the 7 variants down to 4 markers (rs6545816, rs1427407, rs66650371, and rs7482144) each independently contributing HbF-boosting alleles, together accounting for 21.8% of HbF variability (r2) in the HbSS or HbSß0 patients. The model was replicated with consistent r2 in 2 different cohorts: 27.5% in HbSC patients (N = 186) and 23% in 994 Tanzanian HbSS patients. g(HbF), our 4-variant model, provides a robust approach to account for the genetic component of HbF in SCD and is of potential utility in sickle genetic and clinical studies.

Trajectories of dementia-related cognitive decline in a large mental health records derived patient cohort.

BACKGROUND: Modeling trajectories of decline can help describe the variability in progression of cognitive impairment in dementia. Better characterisation of these trajectories has significant implications for understanding disease progression, trial design and care planning. METHODS: Patients with at least three Mini-mental State Examination (MMSE) scores recorded in the South London and Maudsley NHS Foundation Trust Electronic Health Records, UK were selected (N = 3441) to form a retrospective cohort. Trajectories of cognitive decline were identified through latent class growth analysis of longitudinal MMSE scores. Demographics, Health of Nation Outcome Scales and medications were compared across trajectories identified. RESULTS: Four of the six trajectories showed increased rate of decline with lower baseline MMSE. Two trajectories had similar initial MMSE scores but different rates of decline. In the faster declining trajectory of the two, a higher incidence of both behavioral problems and sertraline prescription were present. CONCLUSIONS: We find suggestive evidence for association of behavioral problems and sertraline prescription with rate of decline. Further work is needed to determine whether trajectories replicate in other datasets.